From 076f0465163f79d289cc3ffcaa92f97e6668592b Mon Sep 17 00:00:00 2001 From: Thomas Rauter Date: Thu, 19 Sep 2024 15:35:03 +0200 Subject: [PATCH] now build pkdown website --- README.Rmd | 2 +- README.md | 2 +- docs/404.html | 20 +- docs/CODE_OF_CONDUCT.html | 21 +- docs/LICENSE-text.html | 21 +- docs/apple-touch-icon-120x120.png | Bin 0 -> 10626 bytes docs/apple-touch-icon-152x152.png | Bin 0 -> 15392 bytes docs/apple-touch-icon-180x180.png | Bin 0 -> 20080 bytes docs/apple-touch-icon-60x60.png | Bin 0 -> 3802 bytes docs/apple-touch-icon-76x76.png | Bin 0 -> 5392 bytes docs/apple-touch-icon.png | Bin 0 -> 20080 bytes docs/articles/Docker-instructions.html | 237 +++++ docs/articles/Docker_permission_denied.html | 29 +- .../articles/design_limma_design_formula.html | 273 ++++++ docs/articles/get-started.html | 884 ++++++++++------- docs/articles/index.html | 27 +- docs/authors.html | 29 +- docs/example_report.html | 74 -- docs/favicon-16x16.png | Bin 0 -> 965 bytes docs/favicon-32x32.png 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docs/reference/process_combo_pair.html create mode 100644 docs/reference/process_config_column.html create mode 100644 docs/reference/process_enrichment_results.html create mode 100644 docs/reference/process_field.html create mode 100644 docs/reference/process_level_cluster.html create mode 100644 docs/reference/process_plots.html create mode 100644 docs/reference/process_result.html create mode 100644 docs/reference/process_top_table.html create mode 100644 docs/reference/process_within_level.html create mode 100644 docs/reference/read_section_texts.html create mode 100644 docs/reference/remove_batch_effect.html create mode 100644 docs/reference/remove_batch_effect_cluster_hits.html create mode 100644 docs/reference/remove_prefix.html create mode 100644 docs/reference/run_gsea.html create mode 100644 docs/reference/run_limma_splines.html create mode 100644 docs/reference/screen_limma_hyperparams.html create mode 100644 docs/reference/set_default_params.html create mode 100644 docs/reference/shorten_names.html create mode 100644 docs/reference/store_hits.html create mode 100644 docs/reference/truncate_row_names.html create mode 100644 docs/reference/update_splineomics.html create mode 100644 docs/reference/within_level.html diff --git a/README.Rmd b/README.Rmd index a2acdb9..afdeb96 100755 --- a/README.Rmd +++ b/README.Rmd @@ -187,7 +187,7 @@ If you face "permission denied" issues on Linux distributions, check this [vigne ### Tutorial -[This tutorial](https://csbg.github.io/SplineOmics/docs/get-started.html) +[This tutorial](https://csbg.github.io/SplineOmics/docs/articles/get-started.html) covers a real CHO cell time-series proteomics example from start to end. To open an R Markdown file of the **tutorial** in `RStudio`, run: diff --git a/README.md b/README.md index 7cf6ad5..3816527 100755 --- a/README.md +++ b/README.md @@ -229,7 +229,7 @@ this ### Tutorial [This -tutorial](https://csbg.github.io/SplineOmics/docs/get-started.html) +tutorial](https://csbg.github.io/SplineOmics/docs/articles/get-started.html) covers a real CHO cell time-series proteomics example from start to end. To open an R Markdown file of the **tutorial** in `RStudio`, run: diff --git a/docs/404.html b/docs/404.html index 7ad4116..158a05d 100755 --- a/docs/404.html +++ b/docs/404.html @@ -18,14 +18,13 @@ - - +
- +
@@ -103,16 +105,16 @@

Page not found (404)

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/docs/CODE_OF_CONDUCT.html b/docs/CODE_OF_CONDUCT.html index 96a01d6..bf17ad2 100755 --- a/docs/CODE_OF_CONDUCT.html +++ b/docs/CODE_OF_CONDUCT.html @@ -1,9 +1,9 @@ -Contributor Covenant Code of Conduct • SplineOmicsContributor Covenant Code of Conduct • SplineOmics - +
- +
@@ -136,15 +139,15 @@

Attribution -

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 5853ff5..ea6fd05 100755 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -1,9 +1,9 @@ -License • SplineOmicsLicense • SplineOmics - +
- +
@@ -92,15 +95,15 @@

License

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

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+
+ + + + +
+
+
+

Docker-instructions

+

Thomas +Rauter

+ +

2024-09-19

+ + + + +
+ + + + +
+

Pulling the Docker Container +

+

Pull Docker container:

+
# Docker Hub repo still private, will make it public then
+docker pull thomasrauter/splineomics:0.1.0
+

If you face ‘permission denied’ issues, check out this +vignette

+
+
+

Running the Docker Container +

+

To run the Docker container, you can use one of the +following commands, depending on your operating System. The respective +command needs to be run in a folder where the subfolders +input and output exist. Place your data and +meta (and annotation) files in input, and receive your +output from the container in the output folder.

+

For Linux and macOS:

+
# Bash
+docker run -it -d \
+    -v $(pwd)/input:/home/rstudio/input \
+    -v $(pwd)/output:/home/rstudio/output \
+    -p 8888:8787 \
+    -e PASSWORD=123 \
+    --name splineomics \
+    thomasrauter/splineomics:0.1.0
+

For Windows:

+
# PowerShell
+docker run -it -d `
+    -v "${PWD}\input:/home/rstudio/input" `
+    -v "${PWD}\output:/home/rstudio/output" `
+    -p 8888:8787 `
+    -e PASSWORD=123 `
+    --name splineomics `
+    thomasrauter/splineomics:0.1.0
+

Once the container is running, open a web browser and navigate to http://localhost:8888. Use +rstudio as the username and the password you set with the -e +PASSWORD=123 option.

+

As long as the container is running, you can work on that localhost +page with RStudio, where also the SplineOmics package is +installed. /home/rstudio/ is your R session working +folder.

+

Direct all generated results to /home/rstudio/output, +which is mounted to your local folder output. Your results +will be there.

+

Stop the container:

+
docker stop splineomics
+

Start the container again:

+
docker start splineomics
+
+
+

Inspect Docker container installations +

+

To see all the R packages and system installations that make up the +Docker container, you can run the following command in the terminal of +RStudio on your localhost browser page.

+
cp -r /log home/rstudio/output
+

Because the /home/rstudio/output dir is mounted to your +local filesystem, this will make the installation log files available +there.

+
+
+ + + +
+ + + +
+

+

Developed by Thomas Rauter.

+
+ +
+

+

Site built with pkgdown 2.1.0.

+
+ +
+
+ + + + + + + + diff --git a/docs/articles/Docker_permission_denied.html b/docs/articles/Docker_permission_denied.html index 5421cc4..1b9ce1e 100755 --- a/docs/articles/Docker_permission_denied.html +++ b/docs/articles/Docker_permission_denied.html @@ -5,7 +5,7 @@ -Docker permission denied • SplineOmics +Docker_permission_denied • SplineOmics @@ -17,16 +17,14 @@ - - - + - +
- +
-

Docker permission denied

+

Docker_permission_denied

Thomas Rauter

10 June, 2024

- +
@@ -143,16 +144,16 @@

10 June, 2024

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/docs/articles/design_limma_design_formula.html b/docs/articles/design_limma_design_formula.html new file mode 100644 index 0000000..a8a0c02 --- /dev/null +++ b/docs/articles/design_limma_design_formula.html @@ -0,0 +1,273 @@ + + + + + + + +Designing a Limma Design Formula • SplineOmics + + + + + + + + + + + + + + + + + +
+
+ + + + +
+
+
+

Designing a Limma Design Formula

+

Your Name

+ + + + + +
+ + + +
+

Introduction +

+

The limma package is a powerful tool for analyzing gene +expression data, particularly in the context of microarrays and RNA-seq. +A critical part of any limma analysis is the design +formula, which specifies the experimental conditions and contrasts that +you are interested in. This vignette provides a guide on how to +construct a limma design formula correctly, with examples +and best practices.

+
+
+

Understanding the Design Matrix +

+

The design matrix is a crucial component in any differential +expression analysis using limma. It defines the +relationships between the samples and the experimental conditions +(factors) under investigation. A well-constructed design matrix allows +limma to correctly model the effects of these factors and +estimate the differential expression.

+
+

Basic Design Formula +

+

In its simplest form, the design formula includes only one factor, +such as treatment vs. control. If your experiment involves comparing two +conditions (e.g., treated vs. untreated), you +can create a design formula like this:

+
+design <- model.matrix(~ 0 + condition, data = meta)
+

Here, condition is a factor variable in your metadata (meta) that +represents the experimental groups.

+

Important Points: The ~ 0 + condition syntax tells R to create a +design matrix without an intercept (i.e., a matrix where each level of +the factor condition is represented by its own column). This approach is +helpful when you want to make direct comparisons between conditions. +Including Multiple Factors If your experiment includes more than one +factor, such as time points and treatments, you can include both in the +design formula:

+
+design <- model.matrix(~ 0 + treatment + time, data = meta)
+

This formula assumes that the effects of treatment and time are +additive (no interaction). If you suspect that the interaction between +treatment and time might be important, you can include an interaction +term:

+
+design <- model.matrix(~ 0 + treatment * time, data = meta)
+

Interaction Term: The treatment * time term includes both the main +effects of treatment and time and their interaction. Blocking Factors In +some experiments, you might have technical or biological replicates, or +other blocking factors (e.g., batch effects). You can include these +blocking factors in your design formula:

+
+design <- model.matrix(~ 0 + treatment + batch, data = meta)
+

This formula accounts for both treatment and batch effects, ensuring +that your analysis is not confounded by batch effects.

+
+
+
+

Creating Contrasts +

+

After defining your design matrix, you will likely want to make +specific comparisons between conditions. This is where contrasts come +in. For example, to compare treated vs. untreated, you can define a +contrast matrix:

+
+contrast <- makeContrasts(
+  treated_vs_untreated = treatmenttreated - treatmentuntreated,
+  levels = design
+)
+
+
+

Practical Example +

+

Let’s say you have an experiment with two treatments (A and B) and +two time points (early and late). Your metadata might look like +this:

+
+meta <- data.frame(
+  sample = c("S1", "S2", "S3", "S4"),
+  treatment = factor(c("A", "A", "B", "B")),
+  time = factor(c("early", "late", "early", "late"))
+)
+

Your design formula would be:

+
+design <- model.matrix(~ 0 + treatment * time, data = meta)
+

And a contrast to compare treatment A at the early time point against +treatment B at the late time point would be:

+
+contrast <- makeContrasts(
+  A_early_vs_B_late = (treatmentA:timeearly) - (treatmentB:timelate),
+  levels = design
+)
+
+
+

Summary +

+
    +
  1. +Intercept or No Intercept: +
      +
    • Starting with ~ 0 means no intercept (i.e., not +including a baseline group in the model).
      • +
    • Starting with ~ 1 (or just ~) includes an +intercept (baseline group).
      • +
    +
    2. +
  2. +Additive Factors: +
      +
    • Factors separated by + indicate additive effects. For +example, ~ 0 + factor1 + factor2 means you are modeling the +effects of factor1 and factor2 additively, +without considering interactions.
      • +
    +
    3. +
  3. +Interaction Terms: +
      +
    • The * symbol is used to model interactions between +factors. For example, ~ 0 + factor1 * factor2 will include +factor1, factor2, and their interaction +(factor1:factor2).
      • +
    • Alternatively, you can specify the interaction explicitly with +:. For example, +~ 0 + factor1 + factor2 + factor1:factor2 is equivalent to +~ 0 + factor1 * factor2.
      • +
    +
    4. +
+
+

Some examples: +

+
    +
  • +~ 0 + factor1 + factor2: Additive model without an +intercept.
    • +
  • +~ 1 + factor1 + factor2: Additive model with an +intercept.
    • +
  • +~ 0 + factor1 * factor2: Model with main effects and +their interaction, no intercept.
    • +
  • +~ 1 + factor1 * factor2: Model with intercept, main +effects, and their interaction.
    • +
+
+
+
+ + + +
+ + + +
+

+

Developed by Thomas Rauter.

+
+ +
+

+

Site built with pkgdown 2.1.0.

+
+ +
+
+ + + + + + + + diff --git a/docs/articles/get-started.html b/docs/articles/get-started.html index cbe0fa0..a59df02 100755 --- a/docs/articles/get-started.html +++ b/docs/articles/get-started.html @@ -18,15 +18,13 @@ - - - +
- +
@@ -87,7 +88,7 @@

Thomas

10 June, 2024

- +
@@ -98,77 +99,132 @@

10 June, 2024

About this tutorial

This tutorial intends to showcase and explain the capabilities of the -SplineOmics package by walking through a real and complete example, from -start to the end. The example is a time-series proteomics experiment, in -which CHO cells were cultivated in three bioreactors (three biological -replicates). Both in the exponential and stationary growth phase, -samples were taken from each reactor in triplicates at defined -timepoints relative to a feeding of the cells (60 min before feeding, -and 15, 60, 90, 120, and 240 min after). The goal of this analysis is to -find out which of the 7162 cellular proteins show a significant change -over time after the CHO cells were fed. Further, the hits (proteins with -a significant change over time) are clustered based on their temporal -pattern, and a gene set enrichment analysis is performed with each -cluster to see if there are processes which are up- or downregulated -over time after the feeding.

+SplineOmics package by walking through a real and +complete example, from start to finish.

+
+

Example Overview +

+

The example involves a time-series proteomics +experiment, where CHO (chinese hamster ovary) cells were +cultivated in three bioreactors (three biological replicates). The +experiment includes the following setup:

+
    +
  • Samples were taken both during the exponential and +stationary growth phases.
    • +
  • Samples were collected in triplicates from each reactor at defined +timepoints relative to cell feeding: +
      +
    • 60 minutes before feeding
      • +
    • 15, 60, 90, 120, and 240 minutes after feeding
      • +
    +
    • +
+
+
+

Analysis Goals +

+

The main goals of this analysis are:

+
    +
  • +Identify proteins with significant temporal +changes: Out of 7162 cellular proteins, the objective is to +detect which proteins show a significant change over time after the CHO +cells were fed (i.e., the impact of the feeding).
    • +
  • +Cluster hits based on temporal patterns: The +proteins (hits) with significant temporal changes will be clustered +according to their time-based patterns.
    • +
  • +Perform gene set enrichment analysis: For each +cluster, a gene set enrichment analysis will be performed to determine +if specific biological processes are up- or downregulated after +feeding.
    • +
+

Load the packages 

 library(SplineOmics)
-#>
- +library(readxl)

Load the files

-
-data <- read_excel(system.file("extdata", "data.xlsx", package = "SplineOmics"))
-annotation <- read_excel(system.file("extdata", "annotation.xlsx", package = "SplineOmics"))
-meta <- read_excel(system.file("extdata", "meta.xlsx", package = "SplineOmics"))
+
In this example, the data.xlsx file contains the numeric values (the
+intensities) and also the feature descriptions, such as gene and protein
+name (= annotation part)

+
The file meta.xlsx contains the meta information, which are the
+descriptions of the columns of the numeric values of data.

+
(These example files are part of the package and don’t have to be
+present on your system).

+
Please note that this dataset is an actual experimental dataset, but
+the annotation information, such as gene names, has been removed since
+it is not yet published. Instead, the dataset includes randomly
+generated gene symbols and gene names corresponding to Cricetulus
+griseus (Chinese Hamster) for each row. This is intended to demonstrate
+the functionality of the package.

+
+
+data_excel <- readRDS(system.file(
+  "extdata",
+  "proteomics_data.rds",
+  package = "SplineOmics"
+  ))
 
-print(data)
-#> # A tibble: 7,162 × 36
-#>    E09_TP01_Exponential E10_TP01_Exponential E12_TP01_Exponential
-#>                   <dbl>                <dbl>                <dbl>
-#>  1                 15.3                 15.2                 15.3
-#>  2                 14.5                 14.7                 14.6
-#>  3                 16.0                 16.1                 16.1
-#>  4                 16.2                 16.1                 16.2
-#>  5                 15.1                 15.1                 15.2
-#>  6                 14.6                 14.7                 14.6
-#>  7                 15.0                 15.0                 15.1
-#>  8                 14.8                 14.7                 14.7
-#>  9                 20.5                 20.6                 20.7
-#> 10                 16.4                 16.4                 16.4
-#> # ℹ 7,152 more rows
-#> # ℹ 33 more variables: E09_TP02_Exponential <dbl>, E10_TP02_Exponential <dbl>,
-#> #   E12_TP02_Exponential <dbl>, E09_TP03_Exponential <dbl>,
-#> #   E10_TP03_Exponential <dbl>, E12_TP03_Exponential <dbl>,
-#> #   E09_TP04_Exponential <dbl>, E10_TP04_Exponential <dbl>,
-#> #   E12_TP04_Exponential <dbl>, E09_TP05_Exponential <dbl>,
-#> #   E10_TP05_Exponential <dbl>, E12_TP05_Exponential <dbl>, …

-
-print(annotation)
-#> # A tibble: 7,162 × 6
-#>    `Potential contaminant` Protein.Group         Protein.Ids Protein.Names Genes
-#>    <lgl>                   <chr>                 <chr>       <chr>         <chr>
-#>  1 NA                      A0A8C2MV03;A0A8C2N2L3 A0A8C2MV03… A0A8C2MV03_C… Abhd4
-#>  2 NA                      A0A8C2N4G8            A0A8C2N4G8  A0A8C2N4G8_C… Gbe1 
-#>  3 NA                      G3GR83                G3GR83      G3GR83_CRIGR  Akr1…
-#>  4 NA                      A0A098KX95            A0A098KX95  A0A098KX95_C… Agpa…
-#>  5 NA                      G3HGQ9                G3HGQ9      G3HGQ9_CRIGR  Agpa…
-#>  6 NA                      A0A8C2MM23            A0A8C2MM23  A0A8C2MM23_C… Agpa…
-#>  7 NA                      G3H8X2                G3H8X2      G3H8X2_CRIGR  Agpa…
-#>  8 NA                      A0A8C2MXW6            A0A8C2MXW6… A0A8C2MXW6_C… NA   
-#>  9 NA                      A0A061HUZ2            A0A061HUZ2  A0A061HUZ2_C… H671…
-#> 10 NA                      A0A8C2MC97            A0A8C2MC97  A0A8C2MC97_C… Plcb3
-#> # ℹ 7,152 more rows
-#> # ℹ 1 more variable: First.Protein.Description <chr>

-
-print(meta)
+
+meta <- read_excel(
+  system.file(
+    "extdata",
+    "proteomics_meta.xlsx",
+    package = "SplineOmics"
+    )
+  )
+
+# Extract the annotation part from the dataframe.
+first_na_col <- which(is.na(data_excel[1,]))[1]
+annotation <- data_excel |>
+  dplyr::select((first_na_col + 1):ncol(data_excel)) |>
+  dplyr::slice(-c(1:3))
+
+print(data_excel)
+#> # A tibble: 4,165 × 40
+#>    `Sample ID` `1`   `2`   `3`   `4`   `5`   `6`   `7`   `8`   `9`   `10`  `11` 
+#>    <chr>       <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
+#>  1 Reactor     E09   E10   E12   E09   E10   E12   E09   E10   E12   E09   E10  
+#>  2 Time Point  TP01  TP01  TP01  TP02  TP02  TP02  TP03  TP03  TP03  TP04  TP04 
+#>  3 Phase of F… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo…
+#>  4 NA          15.2… 15.2… 15.3… 15.1… 15.2… 15.0… 15.2… 15.2… 15.2… 15.1… 15.2…
+#>  5 NA          15.0… 15.1… 15.2… 15.1… 15.1… 15.2… 15.2… 15.3… 15.2… 15.1… 15.1…
+#>  6 NA          14.5… 14.7… 14.6… 14.5… 14.6… 14.6… 14.5… 14.6… 14.7… 14.5… 14.6…
+#>  7 NA          16.3… 16.4… 16.4… 16.4… 16.4… 16.4… 16.3… 16.3… 16.4… 16.4… 16.4…
+#>  8 NA          16.7… 16.7… 16.6… 16.7… 16.7… 16.7… 16.7… 16.7… 16.6… 16.6… 16.7…
+#>  9 NA          13.8… 13.7… 13.9… 13.9… 13.9… 13.9… 13.9… 13.9… 13.9… 13.9… 13.9…
+#> 10 NA          21.8… 21.7… 21.6… 21.8… 21.6… 21.5… 21.5… 21.6… 21.5… 21.6… 21.5…
+#> # ℹ 4,155 more rows
+#> # ℹ 28 more variables: `12` <chr>, `13` <chr>, `14` <chr>, `15` <chr>,
+#> #   `16` <chr>, `17` <chr>, `18` <chr>, `19` <chr>, `20` <chr>, `21` <chr>,
+#> #   `22` <chr>, `23` <chr>, `24` <chr>, `25` <chr>, `26` <chr>, `27` <chr>,
+#> #   `28` <chr>, `29` <chr>, `30` <chr>, `31` <chr>, `32` <chr>, `33` <chr>,
+#> #   `34` <chr>, `35` <chr>, `36` <chr>, ...38 <lgl>, Gene_symbol <chr>,
+#> #   Gene_name <chr>
+print(annotation)
+#> # A tibble: 4,162 × 2
+#>    Gene_symbol  Gene_name                                              
+#>    <chr>        <chr>                                                  
+#>  1 LOC113838844 cone-rod homeobox protein-like                         
+#>  2 Wdr83os      WD repeat domain 83 opposite strand                    
+#>  3 Cubn         cubilin                                                
+#>  4 Dynlt1       dynein light chain Tctex-type 1                        
+#>  5 Ostc         oligosaccharyltransferase complex non-catalytic subunit
+#>  6 Unc5cl       unc-5 family C-terminal like                           
+#>  7 Cfl1         cofilin 1                                              
+#>  8 LOC100752202 HEN methyltransferase 1                                
+#>  9 LOC100755162 acyl-coenzyme A synthetase ACSM5, mitochondrial        
+#> 10 LOC100768921 40S ribosomal protein S21                              
+#> # ℹ 4,152 more rows
+print(meta)
 #> # A tibble: 36 × 5
 #>    Sample.ID            Reactor Time.Point Phase        Time
 #>    <chr>                <chr>   <chr>      <chr>       <dbl>
@@ -183,225 +239,367 @@ 
Load the files#>  9 E12_TP03_Exponential E12     TP03       Exponential    60
 #> 10 E09_TP04_Exponential E09     TP04       Exponential    90
 #> # ℹ 26 more rows

+

+
Bring the Inputs into the Standardized Format
+

+
Since data_excel is not in the format required by the
+SplineOmics package, it needs some processing. This can
+be done with a few commands in R, but if your file has a specific
+structure, the function extract_data() can handle this
+automatically.

+

+
File Structure Requirements
+

+
If your file looks like the one used here, where:

+
    
+
  • The data matrix field is on the left
    • 
+
  • The annotation info is on the right
    • 
+
  • These fields are separated by one empty column
    • 
+

+
Then, extract_data() can:

+
    
+
  • 
+Identify the data matrix field and convert it into
+a dataframe.
    • 
+
  • 
+Create column headers from the information written
+in the cells above the respective columns of the data matrix field.
    • 
+
  • 
+Assign rowheaders:
+
      
+
    • If no annotation columns are specified, rowheaders will be
+increasing numbers.
      • 
+
    • If annotation columns are specified (like
+"First.Protein.Description" and "ID" in this
+example), these will be combined to form the rowheaders (feature
+names).
      • 
+
    
+
    • 
+

+

+

+
Usage in Plotting
+

+
The generated rowheaders will be used to label any plots where a
+feature is shown individually, such as:

+
    
+
  • 
+Spline plots with the datapoints from an individual
+feature.
    • 
+

+
+data <- extract_data(
+  data = data_excel,
+  feature_name_columns = c("Gene_name"),
+  user_prompt = FALSE
+  )

+

+

Perform EDA (exploratory data analysis)

-

The first step in analysing data is usually EDA. EDA involves -summarizing the main characteristics of the data, often using plots. -This can involve densitiy distributions, boxplots, PCA, correlation -heatmaps, and more. This process can be carried out by using the package -function explore_data(). The necessary arguments are the data matrix -(data), the meta table (meta), the name of the column that contains the -levels of the experiment (condition) (the levels here are Exponential -and Stationary), and the report_info list, that contains general info -about the analysis. Optional arguments are meta_batch_column and -meta_batch2_column, that allow to specify the column name that contain -batch effect 1 and 2. These columns will be used to run the -removeBatchEffect function of limma to remove the batch effect of the -data for plotting. When at least one batch column is provided like this, -the function will not just generate one EDA HTML report, but two. One -for the uncorrected data, and one for the batch corrected data. These -reports are written either in the current working dir as default -location, or to a location specified with the optional argument -report_dir. The function also returns all plots generated. Lastly, if it -is desired that no report should be generated, the optional argument -report can be set to FALSE.

-
+
The first step in analyzing data is typically Exploratory
+Data Analysis (EDA). EDA involves summarizing the main
+characteristics of the data, often through visualizations.

+

+
Common EDA Plots
+

+
Some common types of EDA plots include:

+
    
+
  • Density distributions
    • 
+
  • Boxplots
    • 
+
  • PCA (Principal Component Analysis)
    • 
+
  • Correlation heatmaps
    • 
+

+

+

+
Using explore_data() for EDA
+

+
The SplineOmics package provides the function
+explore_data() to perform EDA. This function requires the
+following arguments:

+
    
+
  • 
+data: The data matrix.
    • 
+
  • 
+meta: The metadata table.
    • 
+
  • 
+condition: The name of the column in the metadata
+that contains the levels of the experiment (e.g., “Exponential” and
+“Stationary”).
    • 
+
  • 
+report_info: A list that contains general
+information about the analysis.
    • 
+

+

+

+
Optional Arguments
+

+
In addition to the required arguments, explore_data()
+offers several optional arguments:

+
    
+
  • meta_batch_column: The name of the column that
+contains the first batch effect.
    • 
+
  • 
+
    meta_batch2_column: The name of the column that
+contains the second batch effect.
    
+
    If at least one batch column is provided, the function will:
    
+
      
+
    • Use the removeBatchEffect() function from
+limma to remove the batch effect from the data before
+plotting.
      • 
+
    • Generate two EDA HTML reports: one for the uncorrected
+data and one for the batch-corrected
+data.
      • 
+
    
+
    • 
+

+

+

+
Output and Report Options
+

+
    
+
  • By default, the reports are saved in the current working
+directory, but this location can be changed using the
+report_dir argument.
    • 
+
  • The function also returns all plots generated
+during the analysis.
    • 
+
  • If you do not want a report to be generated, you can set the
+report argument to FALSE.
    • 
+

+
 report_info <- list(
   omics_data_type = "PTX",
   data_description = "Proteomics data of CHO cells",
   data_collection_date = "February 2024",
   analyst_name = "Thomas Rauter",
   contact_info = "thomas.rauter@plus.ac.at",
-  project_name = "DGTX")
-
-condition <- "Phase"
-meta_batch_column <- "Reactor"
+  project_name = "DGTX"
+  )
 
-report_dir <- here::here("results", "explore_data")

-
-plots <- explore_data(data = data,
-                      meta = meta,
-                      condition = condition,
-                      report_info = report_info,
-                      meta_batch_column = meta_batch_column,
-                      report_dir = report_dir)

-
You can view the generated analysis report of the
-not-batch-corrected-data here: here

-
The EDA plots can tell you a range of things. The plots in the HTML
-report are grouped into three categories: Distribution and Variability
-Analysis, Time Series Analysis, and Dimensionality Reduction and
-Clustering.

+report_dir <- here::here(
+  "results",
+  "explore_data"
+  )
+
+splineomics <- create_splineomics(
+  data = data,
+  meta = meta,
+  annotation = annotation,
+  report_info = report_info,
+  condition = "Phase",
+  meta_batch_column = "Reactor"
+)
+
+plots <- explore_data(
+  splineomics = splineomics,
+  report_dir = report_dir
+  )
-
-

Find the best hyperparameters -

-

Before we can run the limma spline analysis, we have to find out -which “hyperparameters” are the best. Hyperparameters in this context -are for example degree of freedom, different versions of the data -(outlier removed vs. not removed), different limma design formulas, etc. -Rationally thinking about which combination of hyperparameters to use is -very challenging. Instead, it is often better to just try out a bunch of -combinations and choose the best. The function -screen_limma_hyperparams() does this for you. For each hyperparameter, -you can just specify all the values that you would like to try, and the -function then runs the limma spline analysis with the combinations that -can be formed with the hyperparameters that you specified. Not every -single combo is generated, but instead there are “inner” and “outer” -hyperparameters, and only for all “outer” hyperparameters, all combos -are generated. The “inner” hyperparameters are the adj. p-value -thresholds and the spline parameters. For example, if you have two -different versions of one dataset (one time the full dataset, and one -time the dataset with some potential outliers removed), these are -considered “outer” hyperparameters in this context. The function would -generate all possible comparisons for the “outer” hyperparameters, which -is just a single comparison. Then, for both versions of the data, every -“inner” hyperparameter combo is generated. Lets say you specified -natural cubic splines for both, with a degree of freedom of either 2 or -3. For the adj. p-value threshold, you specified 0.05 or 0.1. For each -version of data, it would test out all combinations of the spline -parameters and the adj. p-value threshold. In this case, this is DoF = -2, thesh = 0.05; DoF = 3, tresh = 0.05; DoF = 2, tresh = 0.1; DoF = 3, -tresh = 0.1.

-
+

+
Finding the Best Hyperparameters
+

+
Before running the limma spline analysis, it is
+important to find the best “hyperparameters”. In this context,
+hyperparameters include:

+
    
+
  • Degree of freedom (DoF)
    • 
+
  • 
+Different versions of the data (e.g., outlier
+removed vs. not removed)
    • 
+
  • Different limma design formulas
    • 
+

+

+
Challenge of Hyperparameter Selection
+

+
Rationally determining the best combination of hyperparameters can be
+very challenging. Instead of manually selecting combinations, it is
+often more effective to try out multiple combinations and choose the
+best-performing one.

+

+

+
Using screen_limma_hyperparams()
+

+
The function screen_limma_hyperparams() automates the
+process of testing different combinations of hyperparameters. Here’s how
+it works:

+
    
+
  • 
+Specify values: For each hyperparameter, you can
+specify all the values you want to test.
    • 
+
  • 
+Run combinations: The function runs the
+limma spline analysis with combinations formed from the
+hyperparameters you’ve provided.
    • 
+

+

+

+
Inner vs. Outer Hyperparameters
+

+
Not every possible combination is generated. Instead, there are
+inner and outer hyperparameters:

+
    
+
  • 
+Outer hyperparameters: These include things like
+different versions of the dataset (e.g., full dataset
+vs. dataset with outliers removed).
+
      
+
    • All possible combinations of outer hyperparameters are
+generated.
      • 
+
    
+
    • 
+
  • 
+Inner hyperparameters: These include
+adjusted p-value thresholds and spline
+parameters (e.g., degree of freedom).
+
      
+
    • For each version of the data (outer hyperparameter), all
+combinations of inner hyperparameters are tested.
      • 
+
    
+
    • 
+

+

+

+
Example
+

+
For example, if you have two versions of a dataset (one full dataset,
+and one with some outliers removed), these versions are considered outer
+hyperparameters. The function will generate comparisons for both
+versions of the dataset.

+
For each version, let’s say you specify the following inner
+hyperparameters:

+
    
+
  • 
+Spline parameters: Natural cubic splines with a
+degree of freedom of either 2 or 3.
    • 
+
  • 
+Adjusted p-value threshold: 0.05 or 0.1.
    • 
+

+
The function will generate and test all combinations of the spline
+parameters and p-value thresholds for both versions of the data:

+
    
+
  • DoF = 2, threshold = 0.05
    • 
+
  • DoF = 3, threshold = 0.05
    • 
+
  • DoF = 2, threshold = 0.1
    • 
+
  • DoF = 3, threshold = 0.1
    • 
+

+
This allows you to systematically explore different combinations and
+select the optimal hyperparameters for your analysis.

+
 data1 <- data 
 meta1 <- meta
 
-# (These are not outliers, just removed to showcase this functionality)
-data2 <- data[, -c(1, 2)]
-meta2 <- meta[-c(1, 2),]
+data2 <- data[, !(colnames(data) %in% c(
+  "E12_TP05_Exponential", 
+  "E10_TP10_Stationary"
+  )
+  )]
+meta2 <- meta[!meta$`Sample.ID` %in% c(
+  "E12_TP05_Exponential", 
+  "E10_TP10_Stationary"
+  ), ]
 
 datas <- list(data1, data2) 
-datas_descr <- c("full_data", "outliers_removed") 
+datas_descr <- c(
+  "full_data",
+  "outliers_removed"
+  ) 
 
 metas <- list(meta1, meta2) 
-designs <- c("~ 1 + Phase*X + Reactor", "~ 1 + X + Reactor") 
+designs <- c(
+  "~ 1 + Phase*X + Reactor",
+  "~ 1 + X + Reactor"
+  ) 
 condition <- "Phase" 
-report_dir <- here::here("results", "hyperparams_screen_reports") 
+report_dir <- here::here(
+  "results",
+  "hyperparams_screen_reports"
+  ) 
 meta_batch_column = "Reactor" 
-pthresholds <- c(0.05, 0.1)
+pthresholds <- c(
+  0.05,
+  0.1
+  )
 
-# Every row a combo to test.
-spline_test_configs <- data.frame(spline_type = c("n", "n", "n", "n"),
-                                  degree = c(NA, NA, NA, NA),
-                                  dof = c(2L, 3L, 4L, 5L),
-                                  knots = I(list(c(NA), c(NA), c(NA), c(NA))),                                                        bknots = I(list(c(NA), c(NA), c(NA), c(NA))))

-
-screen_limma_hyperparams(datas,
-                         datas_descr,
-                         metas,
-                         designs,
-                         condition,
-                         spline_test_configs,
-                         report_info,
-                         report_dir,
-                         pthresholds,
-                         meta_batch_column)

-
To see the output HTML report, click here: here

+# Create a dataframe with combinations of spline parameters to test
+# (every row a combo to test)
+spline_test_configs <- data.frame(
+   # 'n' stands for natural cubic splines, b for B-splines.
+  spline_type = c("n", "n", "b", "b"),  
+  # Degree is not applicable (NA) for natural splines.
+  degree = c(NA, NA, 2L, 4L),           
+  # Degrees of freedom (DoF) to test.
+  # Higher dof means spline can fit more complex patterns.
+  dof = c(2L, 3L, 3L, 4L)         
+)
+
+print(spline_test_configs)
+#>   spline_type degree dof
+#> 1           n     NA   2
+#> 2           n     NA   3
+#> 3           b      2   3
+#> 4           b      4   4
+
+screen_limma_hyperparams(
+  splineomics,
+  datas,
+  datas_descr,
+  metas,
+  designs,
+  spline_test_configs,
+  report_dir,
+  pthresholds,
+  )
+

You can view an example report here

+

This report contains the results for the comparison of the “outer” +hyperparameters data 1 and design (formula) 1 against data 1 and design +2. For both of those, all combinations of the “inner” hyperparameters +are generated (every possible combination of all specified adj. p-value +thresholds and spline configs).

+

The encoding of this is here +(This is part of the output of the screen_limma_hyperparams +function).

+
+

Run limma spline analysis

-

Once we identified the hyperparameters, that are likely the best -ones, we can run the limma spline analysis with them and get the -results.

+

Once we identified the hyperparameters that are likely the best ones, +we can run the limma spline analysis with them and get the results.

+

Lets just assume for now that the new parameters, with which the +SplineOmics object is updated, are the best for this analysis. The +choice depends on the analysis. For example, for this analysis, natural +cubic splines (n) with a dof of two seemed to fit the data best (not +overfitting, but also not underfitting), which was the reason those +spline parameters were chosen.

+
+splineomics <- update_splineomics(
+  splineomics = splineomics,
+  design = "~ 1 + Phase*X + Reactor",
+  data = data2, 
+  meta = meta2,  
+  spline_params = list(
+    spline_type = c("n"),   
+    dof = c(2L)
+    )
+)
 
-design <- "~ 1 + Phase*X + Reactor"     # Chosen limma design
-
-spline_params = list(spline_type = c("n"),  # Chosen spline parameters
-                     dof = c(2L))
-
 # Run the limma spline analysis
-result <- run_limma_splines(data,   # Chosen version of the data
-                            meta,
-                            design,
-                            spline_params = spline_params,
-                            condition)
+splineomics <- run_limma_splines(
+  splineomics
+  )
 #> Interaction terms identified in limma design formula. Selecting mode == integrated. This means that all levels are analysed using the full data.
-#> The time values do not change consistently after the replicates.
-
-
-top_tables1 <- result$time_effect 
-print(top_tables1)
-#> $Phase_Exponential
-#> # A tibble: 7,162 × 9
-#>         X1      X2 AveExpr     F   P.Value adj.P.Val feature_index feature_names
-#>      <dbl>   <dbl>   <dbl> <dbl>     <dbl>     <dbl>         <int> <chr>        
-#>  1  0.136   0.222     20.5  19.4   3.61e-6   0.00990          5683 5683         
-#>  2 -0.177   0.242     20.9  17.1   1.03e-5   0.00990           110 110          
-#>  3  0.0716  0.408     18.5  17.0   1.07e-5   0.00990          3253 3253         
-#>  4  0.0457 -0.216     16.2  16.6   1.30e-5   0.00990          2861 2861         
-#>  5 -0.0365  0.203     17.8  16.6   1.31e-5   0.00990          2514 2514         
-#>  6  0.0707  0.248     21.6  16.6   1.33e-5   0.00990          5321 5321         
-#>  7  0.250   0.154     17.3  16.4   1.46e-5   0.00990          6689 6689         
-#>  8 -0.644  -0.0790    14.3  16.4   1.46e-5   0.00990          6127 6127         
-#>  9 -0.376  -0.408     16.2  16.3   1.50e-5   0.00990           213 213          
-#> 10  0.128  -0.116     15.4  16.3   1.50e-5   0.00990          4067 4067         
-#> # ℹ 7,152 more rows
-#> # ℹ 1 more variable: intercept <dbl>
-#> 
-#> $Phase_Stationary
-#> # A tibble: 7,162 × 9
-#>         X1      X2 AveExpr     F   P.Value adj.P.Val feature_index feature_names
-#>      <dbl>   <dbl>   <dbl> <dbl>     <dbl>     <dbl>         <int> <chr>        
-#>  1 -0.656  -0.375     14.3  26.8   1.85e-7   0.00133          6127 6127         
-#>  2 -0.360  -0.221     15.5  16.2   1.62e-5   0.0345           1465 1465         
-#>  3 -0.313  -0.129     17.6  16.0   1.71e-5   0.0345           2722 2722         
-#>  4 -0.363  -0.107     19.2  15.8   1.92e-5   0.0345           6549 6549         
-#>  5 -1.13   -0.769     11.7  15.3   2.41e-5   0.0345           1231 1231         
-#>  6  0.267   0.0878    14.5  12.8   8.95e-5   0.107            1092 1092         
-#>  7  0.0815 -0.254     13.9  12.3   1.21e-4   0.110            5503 5503         
-#>  8 -0.432  -0.189     15.1  12.3   1.22e-4   0.110            1399 1399         
-#>  9 -0.815  -0.503     16.8  11.9   1.51e-4   0.120            3187 3187         
-#> 10  0.824   0.461     11.3  11.3   2.07e-4   0.148            4277 4277         
-#> # ℹ 7,152 more rows
-#> # ℹ 1 more variable: intercept <dbl>
-
-
-top_tables2 <- result$avrg_diff_conditions 
-print(top_tables2)
-#> $avrg_diff_Exponential_vs_Stationary
-#> # A tibble: 7,162 × 9
-#>    logFC AveExpr     t  P.Value adj.P.Val     B feature_index feature_names
-#>    <dbl>   <dbl> <dbl>    <dbl>     <dbl> <dbl>         <int> <chr>        
-#>  1 -2.85    17.1 -55.5 2.71e-32  1.94e-28  63.2          6548 6548         
-#>  2 -1.26    16.6 -45.8 8.78e-30  3.14e-26  57.8          1156 1156         
-#>  3 -1.51    15.9 -41.5 1.71e-28  4.09e-25  55.0          2623 2623         
-#>  4 -2.63    15.0 -40.7 3.04e-28  5.44e-25  54.4           822 822          
-#>  5 -2.52    15.3 -39.1 1.01e-27  1.44e-24  53.3          4129 4129         
-#>  6 -1.81    16.1 -38.5 1.63e-27  1.95e-24  52.8          1123 1123         
-#>  7 -2.72    14.3 -37.0 5.42e-27  5.55e-24  51.7          1098 1098         
-#>  8 -2.10    14.2 -36.6 7.45e-27  6.67e-24  51.3          3158 3158         
-#>  9 -2.34    16.1 -35.4 2.02e-26  1.61e-23  50.4          3155 3155         
-#> 10 -2.71    14.6 -35.3 2.32e-26  1.66e-23  50.2          2955 2955         
-#> # ℹ 7,152 more rows
-#> # ℹ 1 more variable: intercept <dbl>
-
-
-top_tables3 <- result$interaction_condition_time 
-print(top_tables3) 
-#> $time_interaction_Exponential_vs_Stationary
-#> # A tibble: 7,162 × 9
-#>    PhaseStationary.X1 PhaseStationary.X2 AveExpr     F   P.Value adj.P.Val
-#>                 <dbl>              <dbl>   <dbl> <dbl>     <dbl>     <dbl>
-#>  1             -0.519             0.147     14.1 14.1  0.0000458     0.328
-#>  2              1.51             -0.0622    12.4 12.3  0.000117      0.394
-#>  3              2.71              0.698     12.9 11.7  0.000171      0.394
-#>  4             -0.223             0.210     15.3 10.8  0.000280      0.394
-#>  5              0.967             0.0145    13.5 10.7  0.000298      0.394
-#>  6              0.510             0.115     16.5 10.2  0.000401      0.394
-#>  7              1.13             -0.240     12.3  9.72 0.000538      0.394
-#>  8             -0.121            -0.179     15.9  9.72 0.000539      0.394
-#>  9             -0.311            -0.144     17.3  9.71 0.000542      0.394
-#> 10              0.602             0.302     12.8  9.69 0.000550      0.394
-#> # ℹ 7,152 more rows
-#> # ℹ 3 more variables: feature_index <int>, feature_names <chr>, intercept <dbl>
+#> Column 'Reactor' of meta will be used to remove the batch effect for the plotting +#> Info limma spline analysis completed successfully

The output of the function run_limma_splines() is a named list, where -each element is a specific “category” of results. Each of those elements -is a list, containing as elements the respective limma topTables, either -for each level or each comparison between two levels.

+each element is a specific “category” of results. Refer to this +document for an explanation of the different result categories. Each +of those elements is a list, containing as elements the respective limma +topTables, either for each level or each comparison between two +levels.

The element “time_effect” is a list, where each element is the topTable where the p-value for each feature for the respective level are reported.

@@ -417,14 +615,18 @@

Build limma report
-report_dir <- here::here("results", "create_limma_reports")
+
+report_dir <- here::here(
+  "results",
+  "create_limma_reports"
+  )
 
-create_limma_report(run_limma_splines_result = result,
-                    report_info = report_info,
-                    report_dir = report_dir)

+plots <- create_limma_report(
+  splineomics,
+  report_dir = report_dir
+  )

You can view the generated analysis report of the create_limma_report -function here: here

+function here.

Cluster the hits (significant features) @@ -434,28 +636,43 @@

Cluster the hits (significant fea hit is by setting an adj. p-value threshold for every level. Then, hierarchical clustering is used to place every hit in one of as many clusters as we have specified for that specific level.

-
-adj_pthresholds <- c(0.05, 0.05)   
-clusters <- list(2L, 2L)   
-report_dir <- here::here("results", "clustering_reports")
+
+adj_pthresholds <- c(
+  0.05,
+  0.05
+  )
 
-clustering_results <- cluster_hits(top_tables = top_tables1, 
-                                   data = data, 
-                                   meta = meta, 
-                                   design = design,
-                                   condition = condition, 
-                                   spline_params = spline_params,
-                                   adj_pthresholds = adj_pthresholds,
-                                   clusters = clusters,
-                                   report_info = report_info,
-                                   meta_batch_column = meta_batch_column,
-                                   report_dir = report_dir,
-                                   report = TRUE)
-#> Interaction terms identified in limma design formula. Selecting mode == integrated. This means that all levels are analysed using the full data.
-#> The time values do not change consistently after the replicates.
-#> Column 'Reactor' of meta will be used to remove the batch effect for the plotting
-#> [1] "Generating report. This takes a few seconds."

-
To see the output HTML report, click here: here

+clusters <- c(
+  6L,
+  3L
+  )
+
+report_dir <- here::here(
+  "results",
+  "clustering_reports"
+  )
+
+plot_info = list(
+  y_axis_label = "log2 intensity",
+  time_unit = "min",
+  treatment_labels = c("Feeding"),
+  treatment_timepoints = c(0)
+)
+
+gene_column_name <- "Gene_symbol"
+genes <- data_excel[[gene_column_name]][4:nrow(data_excel)]
+
+clustering_results <- cluster_hits(
+  splineomics = splineomics,
+  analysis_type = "time_effect",
+  adj_pthresholds = adj_pthresholds,
+  clusters = clusters,
+  genes = genes,
+  plot_info = plot_info,
+  report_dir = report_dir,
+  )
+

You can view the generated analysis report of the cluster_hits +function here.

Perform gene set enrichment analysis (GSEA) @@ -463,58 +680,61 @@

Perform gene set enrichment a

To each clustered hit, the respective gene can be assigned and GSEA performed. For this, the Enrichr databases of choice have to be downloaded:

-
-gene_set_lib <- c("WikiPathways_2019_Human",
-                  "NCI-Nature_2016",
-                  "TRRUST_Transcription_Factors_2019",
-                  "MSigDB_Hallmark_2020",
-                  "GO_Cellular_Component_2018",
-                  "CORUM",
-                  "KEGG_2019_Human",
-                  "TRANSFAC_and_JASPAR_PWMs",
-                  "ENCODE_and_ChEA_Consensus_TFs_from_ChIP-X",
-                  "GO_Biological_Process_2018",
-                  "GO_Molecular_Function_2018",
-                  "Human_Gene_Atlas")
+
+gene_set_lib <- c(
+  "WikiPathways_2019_Human",
+  "NCI-Nature_2016",
+  "TRRUST_Transcription_Factors_2019",
+  "MSigDB_Hallmark_2020",
+  "GO_Cellular_Component_2018",
+  "CORUM",
+  "KEGG_2019_Human",
+  "TRANSFAC_and_JASPAR_PWMs",
+  "ENCODE_and_ChEA_Consensus_TFs_from_ChIP-X",
+  "GO_Biological_Process_2018",
+  "GO_Molecular_Function_2018",
+  "Human_Gene_Atlas"
+  )
 
 download_enrichr_databases(gene_set_lib)

 
Per default the file is placed in the current working directory,
 which is the root dir of the R project.

-
To run GSEA, a genes vector has to be created, containing all the
-underlying genes of the features. The downloaded database file has to be
-loaded as a dataframe. Further, optionally, the clusterProfiler
-parameters and the report dir can be specified. The function
-create_gsea_report() runs GSEA using clusterProfiler, generates an HTML
-report and returns the GSEA dotplots in R.

-
-# Get gene vector
-gene_column_name <- "Genes"
-genes <- annotation[[gene_column_name]][1:nrow(annotation)]
-genes <- sub(" .*", "", genes)
-genes <- sub(";.*", "", genes)
-genes <- sub("_.*", "", genes)
-genes <- sub("-.*", "", genes)
-
-downloaded_dbs_filepath <- 
+
To run GSEA, the downloaded database file has to be loaded as a
+dataframe. Further, optionally, the clusterProfiler parameters and the
+report dir can be specified. The function create_gsea_report() runs GSEA
+using clusterProfiler, generates an HTML report and returns the GSEA
+dotplots in R.

+
+downloaded_dbs_filepath <-
   here::here("all_databases_08_04_2024-12_41_50.tsv")
-databases <- readr::read_tsv(downloaded_dbs_filepath, col_types = readr::cols())
 
-clusterProfiler_params <- list(adj_p_value = 0.05,
-                               pAdjustMethod = "BH",
-                               minGSSize = 10,
-                               maxGSSize = 500,
-                               qvalueCutoff = 0.2)
+databases <- readr::read_tsv(
+  downloaded_dbs_filepath,
+  col_types = readr::cols()
+  )
+
+clusterProfiler_params <- list(
+  adj_p_value = 0.05,
+  pAdjustMethod = "BH",
+  minGSSize = 10,
+  maxGSSize = 500,
+  qvalueCutoff = 0.2
+  )
 
-report_dir <- here::here("results", "gsea_reports")
+report_dir <- here::here(
+  "results",
+  "gsea_reports"
+  )
 
-result <- create_gsea_report(levels_clustered_hits = 
-                                  clustering_results$clustered_hits_levels,
-                             genes = genes,
-                             databases = databases,
-                             params = clusterProfiler_params,
-                             report_info = report_info,
-                             report_dir = report_dir)

-
To see the output HTML report, click here: here

+result <- create_gsea_report(
+  levels_clustered_hits = clustering_results$clustered_hits_levels,
+  databases = databases,
+  params = clusterProfiler_params,
+  report_info = report_info,
+  report_dir = report_dir
+  )

+
You can view the generated analysis report of the cluster_hits
+function here.

 
Every row in the dotplots is a term from a specific database, and the
 columns are the respective clusters. The color scale contains the info
 about the odds ratio and the size the -log10 adj. p-value. Only terms
@@ -529,9 +749,7 @@ 
Perform gene set enrichment a
 
   
+

@@ -544,16 +762,16 @@

Perform gene set enrichment a

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/docs/articles/index.html b/docs/articles/index.html index 9b90dcd..2030adc 100755 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -1,9 +1,9 @@ -Articles • SplineOmicsArticles • SplineOmics - +
- +
@@ -57,9 +60,11 @@

Articles

All vignettes

-
Docker permission denied
+
Designing a Limma Design Formula
+
+
Docker_permission_denied
-
functions-in-depth
+
Docker-instructions
get-started
@@ -73,15 +78,15 @@

All vignettes

-

Site built with pkgdown 2.0.9.

+

Site built with pkgdown 2.1.0.

- - + + diff --git a/docs/authors.html b/docs/authors.html index 314fddc..b0061ca 100755 --- a/docs/authors.html +++ b/docs/authors.html @@ -1,9 +1,9 @@ -Authors and Citation • SplineOmicsAuthors and Citation • SplineOmics - +
- +
@@ -54,23 +57,23 @@

Authors and Citation

- +
  • -

    Thomas Rauter. Maintainer. +

    Thomas Rauter. Maintainer.

Citation

- +

Rauter T (2024). SplineOmics: Streamlines the process of analysing omics timeseries data with splines. -R package version 0.1.0. +R package version 0.1.0. 

@Manual{,
   title = {SplineOmics: Streamlines the process of analysing omics timeseries data with splines},
@@ -90,15 +93,15 @@ 
Citation

 
 
 

-  
Site built with pkgdown 2.0.9.

+  
Site built with pkgdown 2.1.0.

 

 
       
 
-  
 
 
-  
+
+
 
   
 
diff --git a/docs/example_report.html b/docs/example_report.html
deleted file mode 100755
index 83395e3..0000000
--- a/docs/example_report.html
+++ /dev/null
@@ -1,74 +0,0 @@
-clustered hits
clustered hits | PTX | 16_05_2024-16_55_12

-
-
-
-
-
-
-
-
-
-
-
-
omics data type      
-                                    :PTX
data description     
-                                    :Gene expression levels over time.
data collection date 
-                                    :2024-05-15
analyst name         
-                                    :Thomas Rauter
project name         
-                                    :DGTX
dataset name         
-                                    :CHO Cell Study
limma design         
-                                    :~ 1 + Phase*X + Reactor
method description   
-                                    :Spline analysis for time-series data.
results summary      
-                                    :Identified significant changes in gene expression.
conclusions          
-                                    :Potential biomarkers identified for further validation.
contact info         
-                                    :rauterthomas0@gmail.com

-
 
-        
Table of Contents

-        

-
Level: Exponential

-

-                    Spline-type: Natural cubic
-                    spline

-                    DoF: 2

-                    Knots: NA

-                    Boundary-knots: NA

-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-
Level: Stationary

-

-                    Spline-type: Natural cubic
-                    spline

-                    DoF: 2

-                    Knots: NA

-                    Boundary-knots: NA

-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-Plot
-
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get-started

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Thomas Rauter

-
10 June, 2024

-
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-
About this tutorial

-
This tutorial intends to showcase and explain the capabilities of the
-SplineOmics package by walking through a real and complete example, from
-start to the end. The example is a time-series proteomics experiment, in
-which CHO cells were cultivated in three bioreactors (three biological
-replicates). Both in the exponential and stationary growth phase,
-samples were taken from each reactor in triplicates at defined
-timepoints relative to a feeding of the cells (60 min before feeding,
-and 15, 60, 90, 120, and 240 min after). The goal of this analysis is to
-find out which of the 7162 cellular proteins show a significant change
-over time after the CHO cells were fed (= impact of the feeding).
-Further, the hits (proteins with a significant change over time) are
-clustered based on their temporal pattern, and a gene set enrichment
-analysis is performed with each cluster to see if there are processes
-which are up- or downregulated over time after the feeding.

-

-

-
Load the packages

-
library(SplineOmics)
-library(readxl)

-

-

-
Load the files

-
In this example, the data.xlsx file contains the numeric values (the
-intensities) and also the feature descriptions, such as gene and protein
-name (= annotation part)

-
The file meta.xlsx contains the meta information, which are the
-descriptions of the columns of the numeric values of data.

-
(These example files are part of the package and don’t have to be
-present on your system).

-
Please note that this dataset is an actual experimental dataset, but
-the annotation information, such as gene names, has been removed since
-it is not yet published. Instead, the dataset includes randomly
-generated gene symbols and gene names corresponding to Cricetulus
-griseus (Chinese Hamster) for each row. This is intended to demonstrate
-the functionality of the package.

-
data_excel <- 
-  read_excel(
-    system.file(
-      "extdata",
-      "proteomics_data.xlsx",
-      package = "SplineOmics"
-      )
-    )
-#> New names:
-#> • `` -> `...38`
-meta <- read_excel(
-  system.file(
-    "extdata",
-    "proteomics_meta.xlsx",
-    package = "SplineOmics"
-    )
-  )
-
-# Extract the annotation part from the dataframe.
-first_na_col <- which(is.na(data_excel[1,]))[1]
-annotation <- data_excel |>
-  dplyr::select((first_na_col + 1):ncol(data_excel)) |>
-  dplyr::slice(-c(1:3))
-
-print(data_excel)
-#> # A tibble: 7,165 × 40
-#>    `Sample ID` `1`   `2`   `3`   `4`   `5`   `6`   `7`   `8`   `9`   `10`  `11` 
-#>    <chr>       <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
-#>  1 Reactor     E09   E10   E12   E09   E10   E12   E09   E10   E12   E09   E10  
-#>  2 Time Point  TP01  TP01  TP01  TP02  TP02  TP02  TP03  TP03  TP03  TP04  TP04 
-#>  3 Phase of F… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo… Expo…
-#>  4 <NA>        15.2… 15.2… 15.3… 15.1… 15.2… 15.0… 15.2… 15.2… 15.2… 15.1… 15.2…
-#>  5 <NA>        14.5… 14.6… 14.5… 14.6… 14.6… 14.6… 14.6… 14.6… 14.6… 14.5… 14.5…
-#>  6 <NA>        15.9… 16.0… 16.0… 16.0… 15.8… 16.0… 15.9… 15.8… 16.0… 15.9… 15.9…
-#>  7 <NA>        16.1… 16.0… 16.1… 16.1… 16.0… 16.1… 16.0… 16.0… 16.0… 15.9… 16.0…
-#>  8 <NA>        15.0… 15.1… 15.2… 15.1… 15.1… 15.2… 15.2… 15.3… 15.2… 15.1… 15.1…
-#>  9 <NA>        14.5… 14.7… 14.6… 14.5… 14.6… 14.6… 14.5… 14.6… 14.7… 14.5… 14.6…
-#> 10 <NA>        15.0… 14.9… 15.1… 15.0… 15.0… 15.1… 14.9… 15.1… 14.9… 15.0… 14.9…
-#> # ℹ 7,155 more rows
-#> # ℹ 28 more variables: `12` <chr>, `13` <chr>, `14` <chr>, `15` <chr>,
-#> #   `16` <chr>, `17` <chr>, `18` <chr>, `19` <chr>, `20` <chr>, `21` <chr>,
-#> #   `22` <chr>, `23` <chr>, `24` <chr>, `25` <chr>, `26` <chr>, `27` <chr>,
-#> #   `28` <chr>, `29` <chr>, `30` <chr>, `31` <chr>, `32` <chr>, `33` <chr>,
-#> #   `34` <chr>, `35` <chr>, `36` <chr>, ...38 <lgl>, Gene_symbol <chr>,
-#> #   Gene_name <chr>
-print(annotation)
-#> # A tibble: 7,162 × 2
-#>    Gene_symbol  Gene_name                               
-#>    <chr>        <chr>                                   
-#>  1 LOC113838844 cone-rod homeobox protein-like          
-#>  2 Bag4         BAG cochaperone 4                       
-#>  3 Aoc3         amine oxidase copper containing 3       
-#>  4 Heatr9       HEAT repeat containing 9                
-#>  5 Wdr83os      WD repeat domain 83 opposite strand     
-#>  6 Cubn         cubilin                                 
-#>  7 Arhgef5      Rho guanine nucleotide exchange factor 5
-#>  8 LOC103158723 40S ribosomal protein S9                
-#>  9 Ncbp2as2     NCBP2 antisense 2 (head to head)        
-#> 10 Dynlt1       dynein light chain Tctex-type 1         
-#> # ℹ 7,152 more rows
-print(meta)
-#> # A tibble: 36 × 5
-#>    Sample.ID            Reactor Time.Point Phase        Time
-#>    <chr>                <chr>   <chr>      <chr>       <dbl>
-#>  1 E09_TP01_Exponential E09     TP01       Exponential   -60
-#>  2 E10_TP01_Exponential E10     TP01       Exponential   -60
-#>  3 E12_TP01_Exponential E12     TP01       Exponential   -60
-#>  4 E09_TP02_Exponential E09     TP02       Exponential    15
-#>  5 E10_TP02_Exponential E10     TP02       Exponential    15
-#>  6 E12_TP02_Exponential E12     TP02       Exponential    15
-#>  7 E09_TP03_Exponential E09     TP03       Exponential    60
-#>  8 E10_TP03_Exponential E10     TP03       Exponential    60
-#>  9 E12_TP03_Exponential E12     TP03       Exponential    60
-#> 10 E09_TP04_Exponential E09     TP04       Exponential    90
-#> # ℹ 26 more rows

-

-

-
Bring the inputs into the standardized (required) format

-
Since data_excel is not in the format that is required by the
-SplineOmics package, it still needs some processing. This can be with a
-few commands in R, but if your file looks like the one here, with the
-data matrix field on the left and the annotation info on the right,
-separated by one empty column, then the function extract_data() can do
-this processing automatically. It identifies this data matrix field, and
-puts it into a dataframe. The column headers are made up of all the
-infos that are written in the cells above the respective column of this
-data matrix field. The rowheaders are increasing numbers if no
-annotation columns were specified. In this example, the annotation
-columns “First.Protein.Description” and “ID” are specified so that these
-are combined and form the rowheaders (feature names). They will be used
-to label any plots were a feature is shown individually (such as the
-spline plots with the datapoints from an individual feature).

-
data <- extract_data(
-  data = data_excel,
-  feature_name_columns = c("Gene_name"),
-  user_prompt = FALSE
-  )

-

-

-
Perform EDA (exploratory data analysis)

-
The first step in analysing data is usually EDA. EDA involves
-summarizing the main characteristics of the data, often using plots.
-This can involve densitiy distributions, boxplots, PCA, correlation
-heatmaps, and more. This process can be carried out by using the package
-function explore_data(). The necessary arguments are the data matrix
-(data), the meta table (meta), the name of the column that contains the
-levels of the experiment (condition) (the levels here are Exponential
-and Stationary), and the report_info list, that contains general info
-about the analysis. Optional arguments are meta_batch_column and
-meta_batch2_column, that allow to specify the column name that contain
-batch effect 1 and 2. These columns will be used to run the
-removeBatchEffect function of limma to remove the batch effect of the
-data for plotting. When at least one batch column is provided like this,
-the function will not just generate one EDA HTML report, but two. One
-for the uncorrected data, and one for the batch corrected data. These
-reports are written either in the current working dir as default
-location, or to a location specified with the optional argument
-report_dir. The function also returns all plots generated. Lastly, if it
-is desired that no report should be generated, the optional argument
-report can be set to FALSE.

-
report_info <- list(
-  omics_data_type = "PTX",
-  data_description = "Proteomics data of CHO cells",
-  data_collection_date = "February 2024",
-  analyst_name = "Thomas Rauter",
-  contact_info = "thomas.rauter@plus.ac.at",
-  project_name = "DGTX"
-  )
-
-report_dir <- here::here(
-  "results",
-  "explore_data"
-  )

-
splineomics <- create_splineomics(
-  data = data,
-  meta = meta,
-  annotation = annotation,
-  report_info = report_info,
-  condition = "Phase",
-  meta_batch_column = "Reactor"
-)

-
plots <- explore_data(
-  splineomics = splineomics,
-  report_dir = report_dir
-  )

-
You can view the generated analysis report of the
-not-batch-corrected-data here: here

-
The EDA plots can tell you a range of things. The plots in the HTML
-report are grouped into three categories: Distribution and Variability
-Analysis, Time Series Analysis, and Dimensionality Reduction and
-Clustering.

-
If you look at the correlation heatmaps in the HTML report, you can
-see that the samples E12_TP05_Exponential and E10_TP10_Stationary stick
-out. Seeing this, you might want to remove them from the data. You can
-test out what happens when you do this, along with testing how other
-hyperparameter choices influence the results, with the package function
-screen_limma_hyperparams().

-

-

-
Find the best hyperparameters

-
Before we can run the limma spline analysis, we have to find out
-which “hyperparameters” are the best. Hyperparameters in this context
-are for example degree of freedom, different versions of the data
-(outlier removed vs. not removed), different limma design formulas, etc.
-Rationally thinking about which combination of hyperparameters to use is
-very challenging. Instead, it is often better to just try out a bunch of
-combinations and choose the best. The function
-screen_limma_hyperparams() does this for you. For each hyperparameter,
-you can just specify all the values that you would like to try, and the
-function then runs the limma spline analysis with the combinations that
-can be formed with the hyperparameters that you specified. Not every
-single combo is generated, but instead there are “inner” and “outer”
-hyperparameters, and only for all “outer” hyperparameters, all combos
-are generated. The “inner” hyperparameters are the adj. p-value
-thresholds and the spline parameters. For example, if you have two
-different versions of one dataset (one time the full dataset, and one
-time the dataset with some potential outliers removed), these are
-considered “outer” hyperparameters in this context. The function would
-generate all possible comparisons for the “outer” hyperparameters, which
-is just a single comparison. Then, for both versions of the data, every
-“inner” hyperparameter combo is generated. Lets say you specified
-natural cubic splines for both, with a degree of freedom of either 2 or
-3. For the adj. p-value threshold, you specified 0.05 or 0.1. For each
-version of data, it would test out all combinations of the spline
-parameters and the adj. p-value threshold. In this case, this is DoF =
-2, thesh = 0.05; DoF = 3, tresh = 0.05; DoF = 2, tresh = 0.1; DoF = 3,
-tresh = 0.1.

-
data1 <- data 
-meta1 <- meta
-
-data2 <- data[, !(colnames(data) %in% c(
-  "E12_TP05_Exponential", 
-  "E10_TP10_Stationary"
-  )
-  )]
-meta2 <- meta[!meta$`Sample.ID` %in% c(
-  "E12_TP05_Exponential", 
-  "E10_TP10_Stationary"
-  ), ]
-
-datas <- list(data1, data2) 
-datas_descr <- c(
-  "full_data",
-  "outliers_removed"
-  ) 
-
-metas <- list(meta1, meta2) 
-designs <- c(
-  "~ 1 + Phase*X + Reactor",
-  "~ 1 + X + Reactor"
-  ) 
-condition <- "Phase" 
-report_dir <- here::here(
-  "results",
-  "hyperparams_screen_reports"
-  ) 
-meta_batch_column = "Reactor" 
-pthresholds <- c(
-  0.05,
-  0.1
-  )
-
-# Every row a combo to test.
-spline_test_configs <- data.frame(
-  spline_type = c("n", "n", "n", "n"),
-  degree = c(NA, NA, NA, NA),
-  dof = c(2L, 3L, 4L, 5L),
-  knots = I(list(c(NA), c(NA), c(NA), c(NA))),                                                        bknots = I(list(c(NA), c(NA), c(NA), c(NA)))
-  )

-
screen_limma_hyperparams(
-  splineomics,
-  datas,
-  datas_descr,
-  metas,
-  designs,
-  spline_test_configs,
-  report_dir,
-  pthresholds,
-  )

-
To see the output HTML report, click here: here

-

-

-
Run limma spline analysis

-
Once we identified the hyperparameters, that are likely the best
-ones, we can run the limma spline analysis with them and get the
-results.

-
splineomics <- update_splineomics(
-  splineomics = splineomics,
-  design = "~ 1 + Phase*X + Reactor",
-  data = data1,  # data1 and meta1 == data and meta that were loaded before. 
-  meta = meta1,  # This is for illustration
-  spline_params = list(
-    spline_type = c("n"),   
-    dof = c(2L)
-    )
-)

-

-# Run the limma spline analysis
-splineomics <- run_limma_splines(
-  splineomics
-  )
-#> Interaction terms identified in limma design formula. Selecting mode == integrated. This means that all levels are analysed using the full data.
-#> Column 'Reactor' of meta will be used to remove the batch effect for the plotting
-#> Info limma spline analysis completed successfully

-
The output of the function run_limma_splines() is a named list, where
-each element is a specific “category” of results. Each of those elements
-is a list, containing as elements the respective limma topTables, either
-for each level or each comparison between two levels.

-
The element “time_effect” is a list, where each element is the
-topTable where the p-value for each feature for the respective level are
-reported.

-
The element “avrg_diff_conditions” is a list that contains as
-elements the topTables, that represent the comparison of the average
-differences of the levels.

-
The element “interaction_condition_time” is a list that contains as
-elements the topTables, that represent the interaction between the
-levels (which includes both time and the average differences)

-

-

-
Build limma report

-
The topTables of all three categories can be used to generate p-value
-histograms an volcano plots.

-
report_dir <- here::here(
-  "results",
-  "create_limma_reports"
-  )
-
-plots <- create_limma_report(
-  splineomics,
-  report_dir = report_dir
-  )

-
You can view the generated analysis report of the create_limma_report
-function here.

-

-

-
Cluster the hits (significant features)

-
After we obtained the limma spline results, we can cluster the hits
-based on their temporal pattern (their spline shape). We define what a
-hit is by setting an adj. p-value threshold for every level. Then,
-hierarchical clustering is used to place every hit in one of as many
-clusters as we have specified for that specific level.

-
adj_pthresholds <- c(
-  0.05,
-  0.05
-  )
-
-clusters <- c(
-  6L,
-  3L
-  )
-
-report_dir <- here::here(
-  "results",
-  "clustering_reports"
-  )
-
-plot_info = list(
-  y_axis_label = "log2 intensity",
-  time_unit = "min",
-  treatment_labels = c("Feeding"),
-  treatment_timepoints = c(0)
-)
-
-gene_column_name <- "Gene_symbol"
-genes <- data_excel[[gene_column_name]][4:nrow(data_excel)]
-
-clustering_results <- cluster_hits(
-  splineomics = splineomics,
-  analysis_type = "time_effect",
-  adj_pthresholds = adj_pthresholds,
-  clusters = clusters,
-  genes = genes,
-  plot_info = plot_info,
-  report_dir = report_dir,
-  )

-
Here you can see a cluster_hits
-report

-

-

-
Perform gene set enrichment analysis (GSEA)

-
To each clustered hit, the respective gene can be assigned and GSEA
-performed. For this, the Enrichr databases of choice have to be
-downloaded:

-
gene_set_lib <- c(
-  "WikiPathways_2019_Human",
-  "NCI-Nature_2016",
-  "TRRUST_Transcription_Factors_2019",
-  "MSigDB_Hallmark_2020",
-  "GO_Cellular_Component_2018",
-  "CORUM",
-  "KEGG_2019_Human",
-  "TRANSFAC_and_JASPAR_PWMs",
-  "ENCODE_and_ChEA_Consensus_TFs_from_ChIP-X",
-  "GO_Biological_Process_2018",
-  "GO_Molecular_Function_2018",
-  "Human_Gene_Atlas"
-  )
-
-download_enrichr_databases(gene_set_lib)

-
Per default the file is placed in the current working directory,
-which is the root dir of the R project.

-
To run GSEA, a genes vector has to be created, containing all the
-underlying genes of the features. The downloaded database file has to be
-loaded as a dataframe. Further, optionally, the clusterProfiler
-parameters and the report dir can be specified. The function
-create_gsea_report() runs GSEA using clusterProfiler, generates an HTML
-report and returns the GSEA dotplots in R.

-
# Modify gene vector
-genes <- sub(" .*", "", genes)
-genes <- sub(";.*", "", genes)
-genes <- sub("_.*", "", genes)
-genes <- sub("-.*", "", genes)
-
-downloaded_dbs_filepath <-
-  here::here("all_databases_08_04_2024-12_41_50.tsv")
-databases <- readr::read_tsv(
-  downloaded_dbs_filepath,
-  col_types = readr::cols()
-  )
-
-clusterProfiler_params <- list(
-  adj_p_value = 0.05,
-  pAdjustMethod = "BH",
-  minGSSize = 10,
-  maxGSSize = 500,
-  qvalueCutoff = 0.2
-  )
-
-report_dir <- here::here(
-  "results",
-  "gsea_reports"
-  )
-
-result <- create_gsea_report(
-  levels_clustered_hits = clustering_results$clustered_hits_levels,
-  genes = genes,
-  databases = databases,
-  params = clusterProfiler_params,
-  report_info = report_info,
-  report_dir = report_dir
-  )

-
Here you can see an gsea
-report

-
Every row in the dotplots is a term from a specific database, and the
-columns are the respective clusters. The color scale contains the info
-about the odds ratio and the size the -log10 adj. p-value. Only terms
-that have > 2 genes as support are included in the plot. Further, for
-each cluster, just maximally 5 terms are shown (the terms with the
-highest odds ratios). Note that when for example cluster 1 already has 5
-terms, and cluster 2 does not, and gets a term which was also found for
-cluster 1, than this term would be included as the sixth term for
-cluster 1, so this is a way the maximum of 5 can be exceeded.

-

-
-
-
-
-
-
-
-
-
-
-
diff --git a/docs/index.html b/docs/index.html
index 488ac69..7dfa450 100755
--- a/docs/index.html
+++ b/docs/index.html
@@ -19,14 +19,13 @@
 
 
 
-
 
 
 
-    
+
 
     

       

 
 
-      
+
 
       

   

 

-
SplineOmics 
+
SplineOmics
 

-
VersionLicense: MIT Maintained? YesR CMD CheckDocker DOI

-
The R package SplineOmics gets the significant features (hits) of time-series omics data by using splines and limma for hypothesis testing and clusters the hits based on the spline shape, showing all results in HTML reports.

+
VersionLicense: MIT Maintained? YesR CMD CheckDocker

+

+
The R package SplineOmics finds the significant features (hits) of time-series -omics data by using splines and limma for hypothesis testing. It then clusters the hits based on the spline shape while showing all results in summary HTML reports.

+
The graphical abstract below shows the full workflow streamlined by SplineOmics:

+

 

 
Table of Contents
 

 
 

 

 
📘 Introduction
 

-
Welcome to SplineOmics, an R package designed to streamline the analysis of omics time-series data, followed by automated HTML report generation.

+
Welcome to SplineOmics, an R package designed to streamline the analysis of -omics time-series data, followed by automated HTML report generation.

 

 
Is the SplineOmics package of use for me?
 

-
If you have omics data over time, the package will help you to run limma with splines, decide on which parameters to use, perform the clustering, run GSEA and show result plots in HTML reports.

+
If you have -omics data over time, the package will help you to run limma with splines, decide on which parameters to use, perform the clustering, run GSEA and show result plots in HTML reports. Any time-series data that is a valid input to the limma package is also a valid input to the SplineOmics package (such as transcriptomics, proteomics, phosphoproteomics, metabolomics, glycan fractional abundances, etc.).

 

 

 
What do I need precisely?
 

 
    
-
  1. A data matrix where each row is a feature (e.g., protein, metabolite, etc.) and each column is a sample taken at a specific time.
    2. 
-
  2. A table with metadata on the rows/features (e.g., gene and protein name)
    3. 
-
  3. A table with metadata on the columns/samples (e.g., reactor, time point, etc.)
    4. 
+
  4. Data: A data matrix where each row is a feature (e.g., protein, metabolite, etc.) and each column is a sample taken at a specific time.
    5. 
+
  5. Meta: A table with metadata on the columns/samples of the data matrix (e.g., batch, time point, etc.)
    6. 
+
  6. Annotation: A table with identifiers on the rows/features of the data matrix (e.g., gene and protein name).
    7. 
 

 

 

@@ -132,8 +144,8 @@ 
Capabilitiesexplore_data() function generates an HTML report, containing various EDA plots, such as densitiy, PCA, and correlation heatmap plots.

+
Automatically perform exploratory data analysis:

+
The explore_data() function generates an HTML report, containing various plots, such as density, PCA, and correlation heatmap plots.

 
 
  • 
 
    Explore various limma splines hyperparameters:
    
@@ -149,11 +161,11 @@ 
    Capabilitiescreate_gsea_report() function.
    
+
    Perform gene set enrichment analysis (GSEA) using the clustered hits with the create_gsea_report() function.
    
 
    • 
 
  • 
 
    Generate reports:
    
-
    Automatically generate reports to showcase all results.
    
+
    Automatically generate reports to showcase all results. See an example report of the cluster_hits() function here.
    
 
    • 
 
 
    
@@ -161,7 +173,7 @@ 
    Capabilities
 
    🔧 Installation
 
    
-
    Follow these steps to install the SplineOmics package from its GitHub repository into your R environment.
    
+
    Follow the steps below to install the SplineOmics package from the GitHub repository into your R environment.
    
 
    
 
    Prerequisites
 
    
@@ -176,31 +188,66 @@ 
    Installation Steps
 
  • Open RStudio or your R console.
    • 
-
  • 
-
    Install and load remotes, and install SplineOmics from GitHub:
    
-
    Copy and paste the following code block into your R console.
    
+
  • Install SplineOmics from GitHub with all dependencies.
    • 
+
+
    Copy and paste the following code block into your R console or run it as a script.
    
+
    
+
    Note for Windows Users:
    
+Please read the text below this code block before running it!
    
+
    
 
    -# Check if remotes is installed; if not, install it
-if (!requireNamespace("remotes", quietly = TRUE)) {
-  install.packages("remotes")
+# Function to ensure a package is installed
+ensure_installed <- function(pkg) {
+  if (!requireNamespace(pkg, quietly = TRUE)) {
+    install.packages(pkg)
+  }
 }
 
-# Load remotes package
+# Install packages if not already available
+ensure_installed("BiocManager")
+ensure_installed("remotes")
+
+# Load packages
+library(BiocManager)
 library(remotes)
 
-# This line will be deleted once the repo is public
+# Install Bioconductor dependencies
+BiocManager::install(c(
+  "ComplexHeatmap",
+  "limma"
+  ), force = TRUE)
+
+# Delete once repo is public
 Sys.setenv(GITHUB_PAT = "your_GitHub_PAT")
 
-# Install latest SplineOmics version from GitHub
-remotes::install_github("csbg/SplineOmics@main")
    
-
+# Install SplineOmics from GitHub
+remotes::install_github(
+  "csbg/SplineOmics@ad35d9aef2e8a8b19572c83ec771f4d92b343a4e",
+  dependencies = TRUE,  # Install all dependencies
+  force = TRUE,         # Force reinstallation
+  upgrade = "always",   # Always upgrade dependencies
+)
+
+# Verify the installation
+if ("SplineOmics" %in% rownames(installed.packages())) {
+  message("SplineOmics installed successfully.")
+} else {
+  message("SplineOmics installation failed.")
+}
    +

    Note that when some installation paths are not writable on Windows, it is necessary running RStudio as administrator once for the installation. Otherwise, set up a library path (code block below) for the installation and (re)run the code block above.

    +
    +# Create a directory for R libraries
+dir.create("~/Rlibs", showWarnings = FALSE)
+
+# Set the library path to include the new directory
+.libPaths(c("~/Rlibs", .libPaths()))
    +
    1. -

      Load the SplineOmics package:

      +Load the SplineOmics package:
      2. +

    Once the installation is complete, load the SplineOmics package into your R session or script to start using it:

    -
    +
     library(SplineOmics)
    
-
-

    Troubleshooting @@ -208,73 +255,62 @@

    TroubleshootingIf you encounter errors related to dependencies or package versions during installation, try updating your R and RStudio to the latest versions and repeat the installation steps.

    For issues specifically related to the SplineOmics package, check the Issues section of the GitHub repository for similar problems or to post a new issue.

    +
    +

    🐳 Docker Container +

    +

    Alternatively, you can run your analysis in a Docker container. The underlying Docker image encapsulates the SplineOmics package together with the necessary environment and dependencies. This ensures higher levels of reproducibility because the analysis is carried out in a consistent environment, independent of the operating system and its custom configurations.

    +

    More information about Docker containers can be found on the official Docker page.

    +

    For instructions on downloading the image of the SplineOmics package and running the container, please refer to the Docker instructions.

    +
    +

    Troubleshooting +

    +

    If you face “permission denied” issues on Linux distributions, check this vignette.

    +
    +
    -

    🛠️ Usage +

    ▶️ Usage

    -

    📖 Tutorial +

    Tutorial

    -

    This tutorial covers a real CHO cell time-series proteomics example from start to the end.

    +

    This tutorial covers a real CHO cell time-series proteomics example from start to end.

    +

    To open an R Markdown file of the tutorial in RStudio, run:

    +
    +library(SplineOmics)
+open_tutorial()
    +

    To open an R Markdown file in RStudio containing a template for your own analysis, run:

    +
    +library(SplineOmics)
+open_template()
    -

    🔬 Functions in Depth +

    Functions in Depth

    -

    A detailed description of all arguments and outputs of all the available package functions can be found here.

    -
    +

    A detailed description of all arguments and outputs of the available package functions can be found here.

    -
    -

    🐳 Docker Container -

    -

    To facilitate reproducible analysis, we provide a Docker container that encapsulates the SplineOmics package together with the necessary environment and dependencies. Follow the instructions below to pull the Docker container and run your analysis.

    -

    Pulling the Docker Container +

    Design limma design formula

    -

    You can pull the Docker container of the desired version of the SplineOmics package from GitHub using the following command (here it downloads version 0.1.0):

    -
    docker pull ghcr.io/thomas-rauter/splineomics:0.1.0
    +

    A quick guide on how to design a limma design formula can be found here

    +

    An explanation of the three different limma results can be found here

    -

    Running the Docker Container +

    RNA-seq and Glycan Data

    -

    To run the Docker container, you can use one of the following commands, depending on your operating System. The respective command needs to be run in a folder where the subfolders input and output exist. Place your data and meta (and annotation) files in input, and receive your output from the package in the output folder.

    -

    For Linux and macOS:

    -
    # Bash
-docker run -it -d \
-    -v $(pwd)/input:/home/rstudio/input \
-    -v $(pwd)/output:/home/rstudio/output \
-    -p 8888:8787 \
-    -e PASSWORD=123 \
-    --name splineomics \
-    ghcr.io/thomasrauter/splineomics:0.1.0
    -

    For Windows:

    -
    # PowerShell
-docker run -it -d `
-    -v ${PWD}\input:/home/rstudio/input `
-    -v ${PWD}\output:/home/rstudio/output `
-    -p 8888:8787 `
-    -e PASSWORD=123 `
-    --name splineomics `
-    ghcr.io/thomas-rauter/splineomics:0.1.0
    -

    Once the container is running, open a web browser and navigate to http://localhost:8888. Use rstudio as the username and the password you set with the -e PASSWORD=123 option.

    -

    As long as the container is running, you can work on that localhost page with RStudio, where also the SplineOmics package is installed. /home/rstudio/ is your R session working folder.

    -

    Load your inputs for example like this:

    +
    +

    RNA-seq data +

    +

    Transcriptomics data must be preprocessed for limma. This is done by setting the preprocess_rna_seq argument to TRUE (see documentation of create_splineomics() function). Then, the raw RNA-seq counts provided in the data matrix will undergo normalization and transformation. The default normalization is performed using TMM (Trimmed Mean of M-values) normalization via the edgeR::calcNormFactors function, followed by the voom transformation from the limma package to obtain log-transformed counts per million (logCPM) with associated precision weights. If you require a different normalization method, you can supply your custom normalization function.

    +
    +
    +

    Glycan fractional abundance data +

    +

    The glycan fractional abundance data matrix, where each row represents a type of glycan and the columns correspond to timepoints, must be transformed before analysis. This preprocessing step is essential due to the compositional nature of the data. In compositional data, an increase in the abundance of one component (glycan) necessarily results in a decrease in others, introducing a dependency among the variables that can bias the analysis. One way to address this issue is by applying the Centered Log Ratio (CLR) transformation to the data with the clr function from the compositions package:

    -library(here)
-library(readxl)
-data <- readxl::read_excel(here::here("input", "data.xlsx"))
-meta <- readxl::read_excel(here::here("input", "meta.xlsx"))
    -

    Direct all generated results to /home/rstudio/output, which is mounted to your local folder output. Your results will be there.

    -

    Stop the container:

    -
    docker stop splineomics
    -

    Start the container again:

    -
    docker start splineomics
    +library(compositions) +clr_transformed_data <- clr(data_matrix) # use as SplineOmics input
    -
    -

    Inspect Docker container installations -

    -

    To see all the R packages and system installations that make up the Docker container, you can run the following command in the terminal of RStudio on your localhost browser page.

    -
    cp -r /log home/rstudio/output
    -

    Because the /home/rstudio/output dir is mounted to your local filesystem, this will make the installation log files available there.

    @@ -285,40 +321,20 @@

    📦 Dependencies ComplexHeatmap: For creating complex heatmaps with advanced features.
  • -RColorBrewer: For providing color palettes for data visualization.
    • -
  • base64enc: For encoding/decoding base64.
  • -circlize: For circular visualization of data.
    • -
  • -cluster: For clustering algorithms such as hierarchical clustering.
    • -
  • -clusterProfiler: For functional enrichment analysis.
    • -
  • -data.table: For high-performance data manipulation.
    • -
  • dendextend: For extending dendrogram objects in R, allowing for easier manipulation of dendrograms.
  • dplyr: For data manipulation.
  • -fs: For file system operations.
    • -
  • ggplot2: For creating elegant data visualizations using the grammar of graphics.
  • ggrepel: For better label placement in ggplot2.
  • here: For constructing paths to your project’s files.
  • -htmltools: For HTML rendering and output.
    • -
  • -kableExtra: For producing beautiful tables in R Markdown documents.
    • -
  • -knitr: For dynamic report generation in R.
    • -
  • limma: For linear models for microarray data.
  • -magrittr: For piping operators.
    • -
  • openxlsx: For reading, writing, and editing xlsx files.
  • patchwork: For combining multiple ggplot objects into a single plot.
    • @@ -329,42 +345,52 @@

    📦 Dependencies purrr: For functional programming tools.
  • -ragg: For creating high-quality images for graphics devices.
    • -
  • -readr: For reading rectangular data.
    • -
  • -reshape2: For flexible reshaping of data.
    • -
  • rlang: For tools to work with core language features of R and R’s base types.
  • scales: For scale functions for visualization.
  • -stringr: For simplifying the manipulation of strings.
    • -
  • tibble: For creating tidy data frames that are easy to work with.
  • tidyr: For tidying your data.
  • -viridis: For colorblind-friendly color maps.
    • +zip: For combining files into a zip file.
    -

    R Version +

    Optional dependencies

    +

    These dependencies are only necessary for some functions:

      -
    • Recommended: R 4.3.3 or higher -
        -
      • Note: This project was developed using R 4.3.3. While it should be compatible with newer versions, this is the version guaranteed to work as tested.
        • +
      • +edgeR: For preprocessing RNA-seq data in the run_limma_splines() fun.
        • +
      • +clusterProfiler: For the run_gsea() function (gene set enrichment).
        • +
      • +rstudioapi: For the open_tutorial() and open_template() functions.
      -
      • +
    +
    +

    R Version +

    +
      +
    • Recommended: R 4.3.3 or higher

    +

    📚 Further Reading +

    +

    For those interested in gaining a deeper understanding of the methodologies used in the SplineOmics package, here are some recommended publications:

    +
      +

    • Splines: To learn more about splines, you can refer to this review.

      • +

    • limma: To read about the limma R package, you can refer to this publication.

      • +

    • Hierarchical clustering: To get information about hierarchical clustering, you can refer to this web article.

      • +
    +
    +

    ❓ Getting Help

    If you encounter a bug or have a suggestion for improving the SplineOmics package, we encourage you to open an issue on our GitHub repository. Before opening a new issue, please check to see if your question or bug has already been reported by another user. This helps avoid duplicate reports and ensures that we can address problems efficiently.

    -

    For more detailed questions, discussions, or contributions regarding the package’s use and development, please refer to the GitHub Discussions page for SplineOmics. This forum is a great place to ask for help, share your experiences, and connect with the community.

    -

    Thank you for using and contributing to the development of SplineOmics!

    +

    For more detailed questions, discussions, or contributions regarding the package’s use and development, please refer to the GitHub Discussions page for SplineOmics.

    🤝 Contributing @@ -399,7 +425,7 @@

    📜 License🎓 Citation

    The SplineOmics package is currently not published in a peer-reviewed scientific journal or similar outlet. However, if this package helped you in your work, consider citing this GitHub repository.

    -

    To cite this package, you can use the citation information provided in the CITATION.cff file.

    +

    To cite this package, you can use the citation information provided in the inst/CITATION.cff file.

    You can also generate a citation in various formats using the CITATION.cff file by visiting the top right of this repo and clicking on the “Cite this repository” button.

    Also, if you like the package, consider giving the GitHub repository a star. Your support helps us in the continued development and improvement of SplineOmics. Thank you for using our package!

    @@ -414,9 +440,14 @@

    🌟 Contributors skafdasschaf - 🔧 Helped reviewing code, delivered improvement suggestions and scientific guidance to develop the approach.
  • -VSchaepertoens - ✨ Developed the download_enrichr_databases() function and one internal plotting function, as well as some code for the EDA plots, and the overall approach together with Thomas-Rauter.
    • +VSchaepertoens - ✨ Developed one internal plotting function, as well as some code for the exploratory data analysis plots, and the overall approach together with Thomas-Rauter. +
    +

    🙏 Acknowledgements +

    +

    This work was carried out in the context of the DigiTherapeutX project, which was funded by the Austrian Science Fund (FWF). The research was conducted under the supervision of Prof. Nikolaus Fortelny, who leads the Computational Systems Biology working group at the Paris Lodron University of Salzburg, Austria. You can find more information about Prof. Fortelny’s research group here.

    +
    @@ -464,16 +495,16 @@

    Developers

    -

    Site built with pkgdown 2.0.9.

    +

    Site built with pkgdown 2.1.0.

    - - + + diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 0d1bb98..9aac775 100755 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -1,9 +1,9 @@ pandoc: 3.1.11 -pkgdown: 2.0.9 +pkgdown: 2.1.0 pkgdown_sha: ~ articles: + design_limma_design_formula: design_limma_design_formula.html Docker_permission_denied: Docker_permission_denied.html - functions-in-depth: functions-in-depth.html + Docker-instructions: Docker-instructions.html get-started: get-started.html -last_built: 2024-06-13T15:26Z - +last_built: 2024-09-19T13:28Z diff --git a/docs/reference/InputControl.html b/docs/reference/InputControl.html new file mode 100644 index 0000000..510d98f --- /dev/null +++ b/docs/reference/InputControl.html @@ -0,0 +1,893 @@ + +InputControl: A class for controlling and validating inputs — InputControl • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    InputControl: A class for controlling and validating inputs

    + + +
    + +
    +

    InputControl: A class for controlling and validating inputs

    +

    InputControl: A class for controlling and validating inputs

    +
    + + +
    +

    Details

    +

    This class provides methods to validate the inputs of a function.

    + +

    The method performs the following checks:

    +

    * Ensures that both `annotation` and `data` are provided. +* Confirms that `annotation` is a dataframe. +* Verifies that `annotation` and `data` have the same number of rows.

    +

    If any of these checks fail, an informative error message is returned.

    + + +

    - The method first checks if the lengths of designs and +modes + are equal. If not, it raises an error. +- It then checks if modes is NULL, and if so, the method + returns + without performing any further checks. +- For each mode in modes, the method sets self$args$mode +to the + current mode and calls self$check_mode().

    + + +

    The function performs the following checks: +- If `clusters` is an integer or a vector of integers. Otherwise, it + gives an error.

    +

    Check Plot Info

    + + +

    The method performs the following checks:

    +

    * Ensures that `plot_info` is provided and not NULL. +* Confirms that `y_axis_label` is a character vector with maximally 30 + characters. +* Confirms that `time_unit` is a character vector with maximally 15 +characters. +* Validates that `treatment_labels` is either `NA` or a character vector + with each + element being maximally 15 characters long. +* Validates that `treatment_timepoints` is either `NA` or a numeric +vector with the + same length as `treatment_labels` if `treatment_labels` is not `NA`.

    +

    If any of these checks fail, an informative error message is returned.

    + + +

    The method performs the following checks:

    +

    * Ensures that `analysis_mode` is provided and not NULL. +* Confirms that `analysis_mode` is a character vector of length 1. +* Validates that `analysis_mode` matches one of the allowed values.

    +

    If any of these checks fail, an informative error message is returned.

    + + +

    This function performs the following checks: +1. Ensures `feature_name_columns` and `annotation` are not `NULL`. +2. Verifies that each element in `feature_name_columns` is a character + with + a length of 1. +3. Checks that all elements of `feature_name_columns` are valid column +names in the `annotation` data frame.

    +

    Check Report

    + + +

    The function performs the following checks: +- Whether the `report` argument is present. +- If `report` is not a Boolean value (`TRUE` or `FALSE`), it throws +an error.

    +
    +
    +

    Functions

    + +

    • InputControl: This method verifies the spline test configurations and associated +metadata +within the object's arguments. It performs a series of checks on the +configurations, including column verification, spline type validation, +and ensuring that the degrees of freedom (dof) are within acceptable +ranges.

      • +
    +
    +

    See also

    +

    stop for error handling.

    +

    Check Top Tables

    +

    limma

    +

    Check Modes

    +

    This method validates multiple modes by ensuring that the lengths of the +modes and designs are the same. It then iterates through each mode, +sets it +in the class arguments, and calls self$check_mode() to perform +the validation for each mode.

    +

    model.matrix

    +

    Check Multiple Designs and Metas

    +
    + +
    +

    Public fields

    +

    args
    +

    A list of arguments to be validated.

    +

    Initialize an InputControl object

    + + +

    +
    +
    +

    Methods

    + +
    +

    Public methods

    + +

    Inherited methods

    +

    Method new()

    + +
    +

    Usage

    +

    InputControl$new(args)

    +
    + +
    +

    Arguments

    +

    args
    +

    A list of arguments to be validated.

    + + +

    +
    +
    +

    Returns

    +

    A new instance of the InputControl class.

    +

    Automatically Validate All Arguments

    +

    This method automatically validates all arguments by sequentially +calling +various validation methods defined within the class. Each validation +method +checks specific aspects of the input arguments and raises an error if the +validation fails.

    +

    The following validation methods are called in sequence: +- self$check_data_and_meta() +- self$check_datas_and_metas() +- self$check_datas_descr() +- self$check_mode() +- self$check_modes() +- self$check_design_formula() +- self$check_designs_and_metas() +- self$check_spline_params() +- self$check_spline_test_configs() +- self$check_adj_pthresholds() +- self$check_clusters() +- self$check_time_unit() +- self$check_report_dir() +- self$check_padjust_method() +- self$check_report_info() +- self$check_report() +- self$check_feature_name_columns()

    +
    + +

    +

    Method auto_validate()

    + +
    +

    Usage

    +

    InputControl$auto_validate()

    +
    + +
    +

    Returns

    +

    NULL. The function is used for its side effects of validating +input +arguments and raising errors if any validation fails.

    +

    Check Data and Meta

    +
    + +

    +

    Method check_data_and_meta()

    +

    This function checks the validity of the data and meta objects, +ensuring that +data is a matrix with numeric values and that meta is a dataframe +containing +the specified condition column. Additionally, it verifies that the +number of +columns in the data matrix matches the number of rows in the meta +dataframe.

    +

    Usage

    +

    InputControl$check_data_and_meta()

    +
    + +
    +

    Arguments

    +

    data
    +

    A matrix containing numeric values.

    + + +
    meta
    +

    A dataframe containing the metadata, including the 'Time' +column +and the specified condition column.

    + + +
    condition
    +

    A single character string specifying the column name in +the meta dataframe to be checked.

    + + +
    meta_batch_column
    +

    An optional parameter specifying the column name +in the meta dataframe used to remove the batch effect. Default is NA.

    + + +
    data_meta_index
    +

    An optional parameter specifying the index of the +data/meta pair for error messages. Default is NA.

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if all checks pass. Stops execution and returns an +error message if any check fails.

    +

    Check Annotation Consistency

    +
    + +

    +

    Method check_annotation()

    +

    This method checks the consistency of the annotation with the data. +It ensures +that the annotation is a dataframe and that it has the same number +of rows as the data.

    +

    Usage

    +

    InputControl$check_annotation()

    +
    + +
    +

    Returns

    +

    NULL if any required arguments are missing. Otherwise, performs +checks and potentially raises errors if checks fail.

    +

    Check Multiple Data and Meta Pairs

    +
    + +

    +

    Method check_datas_and_metas()

    +

    Iterates over multiple data and meta pairs to validate each pair using +the `check_data_and_meta` function.

    +

    Usage

    +

    InputControl$check_datas_and_metas()

    +
    + +
    +

    Arguments

    +

    datas
    +

    A list of matrices containing numeric values.

    + + +
    metas
    +

    A list of data frames containing metadata.

    + + +
    condition
    +

    A character string specifying the column name in the +meta dataframe to be checked.

    + + +
    meta_batch_column
    +

    An optional parameter specifying the column name +in the meta dataframe used to remove the batch effect. Default is NA.

    + + +
    meta_batch2_column
    +

    An optional parameter specifying the column + name +in the meta dataframe used to remove the second batch effect. Default +is NA.

    + + +

    +
    +
    +

    Returns

    +

    NULL if any check fails, otherwise returns TRUE.

    +

    Check Data Descriptions

    +
    + +

    +

    Method check_datas_descr()

    +

    Validates that the data descriptions are character vectors with each +element +not exceeding 80 characters in length.

    +

    Usage

    +

    InputControl$check_datas_descr()

    +
    + +
    +

    Arguments

    +

    datas_descr
    +

    A character vector of data descriptions.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +
    + +

    +

    Method check_top_tables()

    +

    Validates that the top tables are a list of dataframes and checks each +dataframe using the `check_dataframe` function.

    +

    Usage

    +

    InputControl$check_top_tables()

    +
    + +
    +

    Arguments

    +

    top_tables
    +

    A list of top tables from limma analysis.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +

    Check Mode

    +
    + +

    +

    Method check_mode()

    +

    Validates that the mode is either 'integrated' or 'isolated', which +depends +on the design formula used in limma.

    +

    Usage

    +

    InputControl$check_mode()

    +
    + +
    +

    Arguments

    +

    mode
    +

    A character string specifying the mode.

    + + +

    +
    +
    +

    Returns

    +

    A message indicating the chosen mode if valid; otherwise, an +error +is thrown.

    +
    + +

    +

    Method check_modes()

    + +
    +

    Usage

    +

    InputControl$check_modes()

    +
    + +
    +

    Returns

    +

    NULL. The function is used for its side effects of validating +each +mode and raising errors if any validation fails.

    +

    Check Design Formula

    +
    + +

    +

    Method check_design_formula()

    +

    Validates the design formula ensuring it is a valid character string, +contains allowed characters, includes the intercept term 'X', and +references +columns present in the metadata.

    +

    Usage

    +

    InputControl$check_design_formula()

    +
    + +
    +

    Arguments

    +

    formula
    +

    A character string representing the design formula.

    + + +
    meta
    +

    A data frame containing metadata.

    + + +
    meta_index
    +

    An optional index for the data/meta pair.

    + + +

    +
    +
    +

    Returns

    +

    TRUE if the design formula is valid, otherwise an error is +thrown.

    +
    + +

    +

    Method check_designs_and_metas()

    +

    Iterates over multiple design formulas and corresponding metadata +to validate each pair using the `check_design_formula` function.

    +

    Usage

    +

    InputControl$check_designs_and_metas()

    +
    + +
    +

    Arguments

    +

    designs
    +

    A vector of character strings representing design +formulas.

    + + +
    metas
    +

    A list of data frames containing metadata.

    + + +
    meta_indices
    +

    A vector of optional indices for the data/meta pairs.

    + + +

    +
    +
    +

    Returns

    +

    NULL if any check fails, otherwise returns TRUE.

    +

    Check Spline Parameters

    +
    + +

    +

    Method check_spline_params()

    +

    Validates the spline parameters both generally and depending on the +specified mode.

    +

    Usage

    +

    InputControl$check_spline_params()

    +
    + +
    +

    Arguments

    +

    spline_params
    +

    A list of spline parameters.

    + + +
    mode
    +

    A character string specifying the mode +('integrated' or 'isolated').

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +

    +
    +
    +

    Returns

    +

    Returns `NULL` if any required arguments are mising, otherwise, + called for side effects.

    +

    Check Spline Test Configurations

    +
    + +

    +

    Method check_spline_test_configs()

    + +
    +

    Usage

    +

    InputControl$check_spline_test_configs()

    +
    + +
    +

    Arguments

    +

    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +

    +
    +
    +

    Returns

    +

    Returns `NULL` if any required arguments are mising, otherwise, + called for side effects.

    +

    Check Limma Top Tables Structure

    +

    This function checks if the provided limma top tables data structure +is correctly formatted. It ensures that the data structure contains +exactly three named elements ('time_effect', 'avrg_diff_conditions', +and 'interaction_condition_time') and that each element contains +dataframes with the correct columns and data types.

    +
    + +

    +

    Method check_limma_top_tables()

    + +
    +

    Usage

    +

    InputControl$check_limma_top_tables()

    +
    + +
    +

    Arguments

    +

    self
    +

    An object containing the data structure to check.

    + + +

    +
    +
    +

    Returns

    +

    This function does not return a value. It stops execution +if the data structure does not match the expected format.

    +

    Check Adjusted p-Thresholds

    +
    + +

    +

    Method check_adj_pthresholds()

    +

    This function checks the validity of the adjusted p-thresholds vector, +ensuring that +all elements are numeric, greater than 0, and less than 1. If any of +these +conditions +are not met, the function stops execution and returns an error message +indicating the +offending elements.

    +

    Usage

    +

    InputControl$check_adj_pthresholds()

    +
    + +
    +

    Arguments

    +

    adj_pthresholds
    +

    A numeric vector of adjusted p-thresholds.

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if all checks pass. Stops execution and returns an +error message if any check fails.

    +

    Check Clusters

    +
    + +

    +

    Method check_clusters()

    +

    This function verifies the cluster configurations within the object's +arguments. +It checks if the clusters argument is present and performs validation +on its +content. If no clusters are specified, it defaults to automatic cluster +estimation.

    +

    Usage

    +

    InputControl$check_clusters()

    +
    + + +

    +

    Method check_plot_info()

    +

    This method checks the validity of the `plot_info` list. It ensures that +`y_axis_label` and `time_unit` meet the length constraints, +`treatment_labels` +is either `NA` or a character vector with elements meeting the length +constraint, +and `treatment_timepoints` is either `NA` or a numeric vector with the +same length +as `treatment_labels`.

    +

    Usage

    +

    InputControl$check_plot_info()

    +
    + +
    +

    Returns

    +

    NULL if `plot_info` is not provided or invalid. Otherwise, +performs checks +and potentially raises errors if checks fail.

    +

    Check and Create Report Directory

    +
    + +

    +

    Method check_report_dir()

    +

    This function checks if the specified report directory exists and is a +valid directory. +If the directory does not exist, it attempts to create it. If there are + any +warnings or +errors during directory creation, the function stops execution and +returns +an error message.

    +

    Usage

    +

    InputControl$check_report_dir()

    +
    + +
    +

    Arguments

    +

    report_dir
    +

    A character string specifying the path to the report +directory.

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if the directory exists or is successfully created. +Stops execution +and returns an error message if the directory cannot be created or is not +valid.

    +

    Check Genes Validity

    +
    + +

    +

    Method check_genes()

    +

    This function checks the validity of the `data` and `genes` arguments +within the `self$args` list. It ensures that `genes` is a character +vector, +that neither `data` nor `genes` is `NULL`, and that the length of `genes` +matches the number of rows in `data`.

    +

    Usage

    +

    InputControl$check_genes()

    +
    + +
    +

    Returns

    +

    Returns `TRUE` if all checks pass. Returns `NULL` if any required +arguments are `NULL`. Throws an error if `genes` is not a character +vector +or if the length of `genes` does not match the number of rows in `data`.

    +

    Check p-Adjustment Method

    +
    + +

    +

    Method check_padjust_method()

    +

    This function checks if the provided p-adjustment method is valid. The +valid +methods are: +"holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", and +"none". +If the method +is not one of these, the function stops execution and returns an error + message.

    +

    Usage

    +

    InputControl$check_padjust_method()

    +
    + +
    +

    Arguments

    +

    padjust_method
    +

    A character string specifying the p-adjustment +method. +Valid options +are "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", and +"none".

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if the p-adjustment method is valid. Stops execution + and +returns an error message if the method is invalid.

    +

    Check Report Information

    +
    + +

    +

    Method check_report_info()

    +

    Validates the report information to ensure it contains all mandatory +fields +and adheres to the required formats.

    +

    Usage

    +

    InputControl$check_report_info()

    +
    + +
    +

    Arguments

    +

    report_info
    +

    A named list containing report information.

    + + +

    +
    +
    +

    Returns

    +

    TRUE if the report information is valid; otherwise, an error is +thrown.

    +

    Check Analysis Mode

    +
    + +

    +

    Method check_analysis_type()

    +

    This method checks the validity of the `analysis_mode` argument. +It ensures that +`analysis_mode` is a character vector of length 1 and that it matches + one of the +allowed analysis modes: "time_effect", "avrg_diff_conditions", or +"interaction_condition_time".

    +

    Usage

    +

    InputControl$check_analysis_type()

    +
    + +
    +

    Returns

    +

    NULL if `analysis_mode` is not provided or invalid. Otherwise, +performs checks +and potentially raises errors if checks fail.

    +

    Check Feature Name Columns

    +
    + +

    +

    Method check_feature_name_columns()

    +

    This function checks whether all elements of `feature_name_columns` are +characters of length 1 and whether they are valid column names in the +`annotation` data frame.

    +

    Usage

    +

    InputControl$check_feature_name_columns()

    +
    + +
    +

    Returns

    +

    Returns `NULL` if any required arguments are missing. Throws +an error +if any element of `feature_name_columns` is not a character of length 1 +or if +any element is not a column name in `annotation`. Returns `TRUE` if all + checks +pass.

    +
    + +

    +

    Method check_report()

    +

    This function verifies the `report` argument within the object's +arguments. +It checks if the `report` argument is present and validates its +Boolean value.

    +

    Usage

    +

    InputControl$check_report()

    +
    + + +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    +

    Usage

    +

    InputControl$clone(deep = FALSE)

    +
    + +
    +

    Arguments

    +

    deep
    +

    Whether to make a deep clone.

    + + +

    +
    + +
    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/Level2Functions.html b/docs/reference/Level2Functions.html new file mode 100644 index 0000000..89bc9c2 --- /dev/null +++ b/docs/reference/Level2Functions.html @@ -0,0 +1,439 @@ + +Level2Functions: A class providing level 2 functionalities — Level2Functions • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Level2Functions: A class providing level 2 functionalities

    + + +
    + +
    +

    Level2Functions: A class providing level 2 functionalities

    +

    Level2Functions: A class providing level 2 functionalities

    +
    + + +
    +

    Details

    +

    This class provides various level 2 functionalities, including +methods to check dataframes and spline parameters.

    +
    +
    +

    See also

    +

    InputControl

    +

    Check Data Matrix

    +
    +
    +

    Super classes

    +

    SplineOmics::Level4Functions -> SplineOmics::Level3Functions -> Level2Functions

    +
    +
    +

    Methods

    + +
    +

    Public methods

    + +

    Inherited methods

    +

    Method check_data()

    +

    This function checks the validity of the data matrix, ensuring that it +is a +matrix, contains only numeric values, +has no missing values, and all elements are non-negative. Additionally, it +verifies that no rows or columns are +entirely zeros.

    +

    Usage

    +

    Level2Functions$check_data(data, data_meta_index = NULL)

    +
    + +
    +

    Arguments

    +

    data
    +

    A dataframe containing numeric values.

    + + +
    data_meta_index
    +

    An optional parameter specifying the index of the + data +for error messages. Default is NA.

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if all checks pass. Stops execution and returns an +error +message if any check fails.

    +

    Check Metadata

    +
    + +

    +

    Method check_meta()

    +

    This function checks the validity of the metadata dataframe, ensuring it +contains the 'Time' column, +does not contain missing values, and that the specified condition column + is +valid and of the appropriate type. +Additionally, it checks for an optional batch effect column and prints +messages regarding its use.

    +

    Usage

    +

    Level2Functions$check_meta(
+  meta,
+  condition,
+  meta_batch_column = NULL,
+  meta_batch2_column = NULL,
+  data_meta_index = NULL
+)

    +
    + +
    +

    Arguments

    +

    meta
    +

    A dataframe containing the metadata, including the 'Time' +column.

    + + +
    condition
    +

    A single character string specifying the column name +in the +meta dataframe to be checked.

    + + +
    meta_batch_column
    +

    An optional parameter specifying the column +name in + the meta dataframe used to remove the batch effect. Default is NA.

    + + +
    meta_batch2_column
    +

    An optional parameter specifying the column +name in +the meta dataframe used to remove the batch effect. Default is NA.

    + + +
    data_meta_index
    +

    An optional parameter specifying the index of the +data/meta pair for error messages. Default is NA.

    + + +

    +
    +
    +

    Returns

    +

    Returns TRUE if all checks pass. Stops execution and returns an +error message if any check fails.

    +

    Check Dataframe

    +
    + +

    +

    Method check_dataframe()

    +

    Validates that the dataframe contains all required columns with the +correct data types.

    +

    Usage

    +

    Level2Functions$check_dataframe(df)

    +
    + +
    +

    Arguments

    +

    df
    +

    A dataframe to check.

    + + +

    +
    +
    +

    Returns

    +

    TRUE if the dataframe is valid, otherwise an error is thrown.

    +

    Check Spline Parameters Generally

    +
    + +

    +

    Method check_spline_params_generally()

    +

    Validates the general structure and contents of spline parameters.

    +

    Usage

    +

    Level2Functions$check_spline_params_generally(spline_params)

    +
    + +
    +

    Arguments

    +

    spline_params
    +

    A list of spline parameters.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +

    Check Spline Parameters Mode Dependent

    +
    + +

    +

    Method check_spline_params_mode_dependent()

    +

    Validates the spline parameters depending on the specified mode.

    +

    Usage

    +

    Level2Functions$check_spline_params_mode_dependent(
+  spline_params,
+  mode,
+  meta,
+  condition
+)

    +
    + +
    +

    Arguments

    +

    spline_params
    +

    A list of spline parameters.

    + + +
    mode
    +

    A character string specifying the mode +('integrated' or 'isolated').

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    + +

    Check Columns in Spline Test Configurations

    +
    + +

    +

    Method check_columns_spline_test_configs()

    +

    Validates that the spline test configurations contain the required columns +in the correct order.

    +

    Usage

    +

    Level2Functions$check_columns_spline_test_configs(spline_test_configs)

    +
    + +
    +

    Arguments

    +

    spline_test_configs
    +

    A dataframe containing spline test +configurations.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +
    + +

    +

    Method check_spline_type_column()

    +

    Validates that the 'spline_type' column in the spline test configurations +contains only 'n' or 'b'.

    +

    Usage

    +

    Level2Functions$check_spline_type_column(spline_test_configs)

    +
    + +
    +

    Arguments

    +

    spline_test_configs
    +

    A dataframe containing spline test +configurations.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +
    + +

    +

    Method check_spline_type_params()

    +

    Validates the parameters for each row in the spline test configurations +based on the spline type.

    +

    Usage

    +

    Level2Functions$check_spline_type_params(spline_test_configs)

    +
    + +
    +

    Arguments

    +

    spline_test_configs
    +

    A dataframe containing spline test +configurations.

    + + +

    +
    +
    +

    Returns

    +

    TRUE if all checks pass, otherwise an error is thrown.

    +
    + +

    +

    Method check_max_and_min_dof()

    +

    Validates the degrees of freedom (DoF) for each row in the spline test +configurations based on the metadata.

    +

    Usage

    +

    Level2Functions$check_max_and_min_dof(spline_test_configs, metas)

    +
    + +
    +

    Arguments

    +

    spline_test_configs
    +

    A dataframe containing spline test +configurations.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +

    +
    +
    +

    Returns

    +

    No return value, called for side effects.

    +
    + +

    +

    Method check_columns()

    + +
    +

    Usage

    +

    Level2Functions$check_columns(df, expected_cols)

    +
    + +
    +

    Arguments

    +

    df
    +

    A dataframe to check.

    + + +
    expected_cols
    +

    A character vector of expected column names.

    + + +

    +
    +
    +

    Returns

    +

    This function does not return a value. It stops execution if the +dataframe columns or their classes do not match the expected structure.

    +
    + +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    +

    Usage

    +

    Level2Functions$clone(deep = FALSE)

    +
    + +
    +

    Arguments

    +

    deep
    +

    Whether to make a deep clone.

    + + +

    +
    + +
    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/Level3Functions.html b/docs/reference/Level3Functions.html new file mode 100644 index 0000000..7db2eb9 --- /dev/null +++ b/docs/reference/Level3Functions.html @@ -0,0 +1,245 @@ + +Level3Functions: A class for level 3 utility functions — Level3Functions • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Level3Functions: A class for level 3 utility functions

    + + +
    + +
    +

    Level3Functions: A class for level 3 utility functions

    +

    Level3Functions: A class for level 3 utility functions

    +
    + + +
    +

    Details

    +

    This class provides methods for creating error messages and checking +batch columns.

    + +

    The function verifies that the `voom` object contains the following +components: +- `E`: A matrix of log2-counts per million (logCPM) values. +- `weights`: A matrix of observation-specific weights that matches the +dimensions of `E`. +- `design`: A matrix representing the design matrix used in the linear +modeling, + with the same number of rows as there are columns in `E`.

    +

    The function also checks for optional components such as: +- `genes`: A data frame of gene annotations. +- `targets`: A data frame of target information. +- `sample.weights`: A numeric vector of sample-specific weights.

    +

    If any of these checks fail, the function stops and reports the issues. +If the structure is valid, a message confirming the validity is printed.

    +
    +
    +

    See also

    +

    Level2Functions

    +

    Check the structure of a voom object

    +
    +
    +

    Super class

    +

    SplineOmics::Level4Functions -> Level3Functions

    +
    +
    +

    Methods

    + +
    +

    Public methods

    + +

    Inherited methods

    +

    Method check_voom_structure()

    +

    This function checks the structure of a `voom` object to ensure that it +contains +all the expected components and that these components have the correct +types +and dimensions. The function does not check the actual data within the +matrices.

    +

    Usage

    +

    Level3Functions$check_voom_structure(voom_obj)

    +
    + +
    +

    Arguments

    +

    voom_obj
    +

    A list representing a `voom` object, typically created +by the + `voom` function from the `limma` package.

    + + +

    +
    +
    +

    Returns

    +

    Boolean TRUE or FALSE. However, the function is mostly called for +its side effects, which stop the script if the structure is not valid.

    +

    Check Batch Column

    +
    + +

    +

    Method check_batch_column()

    +

    This method checks the batch column in the metadata and provides +appropriate messages.

    +

    Usage

    +

    Level3Functions$check_batch_column(meta, meta_batch_column, data_meta_index)

    +
    + +
    +

    Arguments

    +

    meta
    +

    A dataframe containing metadata.

    + + +
    meta_batch_column
    +

    A character string specifying the batch column +in the metadata.

    + + +
    data_meta_index
    +

    An optional parameter specifying the index of the +data/meta pair. Default is NA.

    + + +

    +
    +
    +

    Returns

    +

    NULL. The method is used for its side effects of throwing errors +or printing messages.

    +

    Check Condition Time Consistency

    +
    + +

    +

    Method check_condition_time_consistency()

    +

    This function checks whether the values in the `condition` column +have unique values for each block of identical `Time` values in the +`meta` dataframe. +Additionally, it ensures that every new block of a given time has a +new value +in the `condition` column.

    +

    Usage

    +

    Level3Functions$check_condition_time_consistency(meta, condition)

    +
    + +
    +

    Arguments

    +

    meta
    +

    A dataframe containing the metadata, including the `Time` +column.

    + + +
    condition
    +

    A character string specifying the column name in `meta` +used to define groups for analysis.

    + + +

    +
    +
    +

    Returns

    +

    Logical TRUE if the condition values are consistent with the + time series pattern.

    +
    + +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    +

    Usage

    +

    Level3Functions$clone(deep = FALSE)

    +
    + +
    +

    Arguments

    +

    deep
    +

    Whether to make a deep clone.

    + + +

    +
    + +
    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/Level4Functions.html b/docs/reference/Level4Functions.html new file mode 100644 index 0000000..bc0c3dd --- /dev/null +++ b/docs/reference/Level4Functions.html @@ -0,0 +1,157 @@ + +Level4Functions: A class for level 3 utility functions — Level4Functions • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Level4Functions: A class for level 3 utility functions

    + + +
    + +
    +

    Level4Functions: A class for level 3 utility functions

    +

    Level4Functions: A class for level 3 utility functions

    +
    + + +
    +

    Details

    +

    This class provides methods for creating error messages and checking +batch columns.

    +
    +
    +

    See also

    +

    Level3Functions

    +

    Create Error Message

    +
    +
    +

    Methods

    + +
    +

    Public methods

    + +

    +

    Method create_error_message()

    +

    This method creates a formatted error message that includes the index of +the data/meta pair if provided. +If no index is provided, it returns the message as is.

    +

    Usage

    +

    Level4Functions$create_error_message(message, data_meta_index = NULL)

    +
    + +
    +

    Arguments

    +

    message
    +

    A character string specifying the error message.

    + + +
    data_meta_index
    +

    An optional parameter specifying the index of the +data/meta pair for the error message. Default is NA.

    + + +

    +
    +
    +

    Returns

    +

    Returns a formatted error message string. If an index is provided, +the message includes the index; otherwise, it returns the message as is.

    +
    + +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    +

    Usage

    +

    Level4Functions$clone(deep = FALSE)

    +
    + +
    +

    Arguments

    +

    deep
    +

    Whether to make a deep clone.

    + + +

    +
    + +
    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/NumericBlockFinder.html b/docs/reference/NumericBlockFinder.html new file mode 100644 index 0000000..55ce06f --- /dev/null +++ b/docs/reference/NumericBlockFinder.html @@ -0,0 +1,190 @@ + +NumericBlockFinder: A class for finding numeric blocks in data — NumericBlockFinder • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    NumericBlockFinder: A class for finding numeric blocks in data

    + + +
    + +
    +

    This class provides methods to identify the upper-left and lower-right +cells of a numeric block within a dataframe.

    +
    + + +
    +

    Public fields

    +

    data
    +

    A dataframe containing the input data.

    + + +
    upper_left_cell
    +

    A list containing the row and column indices of the + upper-left cell.

    +

    Initialize a NumericBlockFinder object

    + + +

    +
    +
    +

    Methods

    + +
    +

    Public methods

    + +

    +

    Method new()

    + +
    +

    Usage

    +

    NumericBlockFinder$new(data)

    +
    + +
    +

    Arguments

    +

    data
    +

    A dataframe containing the input data.

    + + +

    +
    +
    +

    Returns

    +

    A new instance of the NumericBlockFinder class.

    +

    Find the upper-left cell of the first 6x6 block of numeric values

    +

    This method identifies the upper-left cell of the first 6x6 block of +numeric values in the dataframe.

    +
    + +

    +

    Method find_upper_left_cell()

    + +
    +

    Usage

    +

    NumericBlockFinder$find_upper_left_cell()

    +
    + +
    +

    Returns

    +

    A list containing the row and column indices of the upper-left + cell.

    +

    Find the lower-right cell of a block of contiguous non-NA values

    +

    This method identifies the lower-right cell of a block of contiguous +non-NA values starting from a given upper-left cell in the dataframe.

    +
    + +

    +

    Method find_lower_right_cell()

    + +
    +

    Usage

    +

    NumericBlockFinder$find_lower_right_cell()

    +
    + +
    +

    Returns

    +

    A list containing the row and column indices of the lower-right + cell.

    +
    + +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    +

    Usage

    +

    NumericBlockFinder$clone(deep = FALSE)

    +
    + +
    +

    Arguments

    +

    deep
    +

    Whether to make a deep clone.

    + + +

    +
    + +
    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/SplineOmics-package.html b/docs/reference/SplineOmics-package.html new file mode 100644 index 0000000..60bd5d5 --- /dev/null +++ b/docs/reference/SplineOmics-package.html @@ -0,0 +1,209 @@ + +Package Name: SplineOmics — SplineOmics-package • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Package Name: SplineOmics

    + + +
    + +
    +

    The R package SplineOmics finds the significant features (hits) of +time-series -omics data by using splines and limma for hypothesis testing. +It then clusters the hits based on the spline shape while showing all +results in summary HTML reports.

    +

    For detailed documentation, vignettes, and examples, please visit the +[SplineOmics GitHub page](https://github.com/csbg/SplineOmics.git).

    +
    + + +
    +

    Key Functions and Classes

    + + +

    - extract_data: Extracts data matrix from Excel file. +- create_splineomics: Creates the SplineOmics object, which contains arguments + used by several package functions. +- explore_data: Performs exploratory data analysis with the data, and outputs + an HTML report containg various plots, such as density plots + and correlation heatmaps. +- screen_limma_hyperparams: Allows the specify lists of different hyperparameters + to test, such as a degree of freedom of 2, 3, 4, + and adj.p-val thresholds, such as 0.1 and 0.05, + and tests all specified different values for all + limma spline hyperparameters in a semi-combinatorial + way. +- update_splineomics: Allows to change values of the SplineOmics object, for + example after observing that outliers should be removed + from the data (update the data parameter). +- run_limma_splines: Central function of the script, is called by the + screen_limma_hyperparams function and can be called to + get the limma spline analysis results (p-values for all + features (e.g. proteins)) with the hyperparameters, that + were selected finally. +- create_limma_report: Creates an HTML report showing the run_limma_splines + results +- cluster_hits: Clusters the splines of the hits (significant features) based + on their shape and shows all results as plots in an HTML + report. +- download_enrichr_databases: Allows to download the Enrichr databases for + runnin clusterProfiler in the run_gsea function + with them. +- run_gsea: Runs clusterProfiler with the clustered hits by using the Enrichr + databases.

    +
    +
    +

    Package Options

    + + +

    None

    +
    +
    +

    Dependencies

    + + +

    - **ComplexHeatmap**: For creating complex heatmaps with advanced features. +- **base64enc**: For encoding/decoding base64. +- **dendextend**: For extending `dendrogram` objects in R, allowing for easier manipulation of dendrograms. +- **dplyr**: For data manipulation. +- **ggplot2**: For creating elegant data visualizations using the grammar of graphics. +- **ggrepel**: For better label placement in ggplot2. +- **here**: For constructing paths to your project’s files. +- **limma**: For linear models for microarray data. +- **openxlsx**: For reading, writing, and editing xlsx files. +- **patchwork**: For combining multiple ggplot objects into a single plot. +- **pheatmap**: For creating pretty heatmaps. +- **progress**: For adding progress bars to your loops and apply functions. +- **purrr**: For functional programming tools. +- **rlang**: For tools to work with core language features of R and R’s base types. +- **scales**: For scale functions for visualization. +- **tibble**: For creating tidy data frames that are easy to work with. +- **tidyr**: For tidying your data. +- **zip**: For combining files into a zip file.

    +

    Optional dependencies

    +

    These dependencies are only necessary for some functions:

    +

    - **edgeR**: For preprocessing RNA-seq data in the run_limma_splines() fun. +- **clusterProfiler**: For the run_gsea() function (gene set enrichment). +- **rstudioapi**: For the open_tutorial() and open_template() functions.

    +
    +
    +

    Authors

    + + +

    - [Thomas-Rauter](https://github.com/Thomas-Rauter) - Wrote the package and + developed the approach with VSchaepertoens under guidance from nfortelny + and skafdasschaf. +- [nfortelny](https://github.com/nfortelny) - Principal Investigator, + provided guidance and support. +- [skafdasschaf](https://github.com/skafdasschaf) - Helped review code and + provided improvement suggestions. +- [VSchaepertoens](https://github.com/VSchaepertoens) - Developed an internal + plotting function and contributed to exploratory data analysis and the + overall approach.

    +
    +
    +

    Maintainer

    + + +

    - Name: Thomas Rauter +- Email: thomas.rauter@plus.ac.at

    +
    +
    +

    License

    + + +

    - License: MIT

    +
    +
    +

    Useful URLs

    + + +

    - [GitHub repo of the package](https://github.com/csbg/SplineOmics.git)

    +
    +
    +

    Additional Information

    + + +

    None

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/add_feature_names.html b/docs/reference/add_feature_names.html new file mode 100644 index 0000000..a1a308e --- /dev/null +++ b/docs/reference/add_feature_names.html @@ -0,0 +1,131 @@ + +Add Feature Names to Data — add_feature_names • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Add Feature Names to Data

    + + +
    + +
    +

    This function assigns feature names to the rows of a dataframe based on a +specified column from another dataframe. If no column is specified, it +assigns sequential numbers as feature names.

    +
    + +
    + 
    add_feature_names(data, clean_data, feature_name_columns)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A dataframe containing the original data with feature names.

    + + +
    clean_data
    +

    A dataframe to which the feature names will be added.

    + + +
    feature_name_columns
    +

    A string specifying the name of the feature +columns in `data`. If `NA`, sequential numbers +will be used as feature names.

    + +
    +
    +

    Value

    +

    The `clean_data` dataframe with updated row names.

    +
    +
    +

    Details

    +

    The function performs the following operations: +- Extracts feature names from the specified column in `data`, ignoring + `NA` values. +- Ensures the feature names are unique and match the number of rows in +`clean_data`. +- Assigns the feature names to the rows of `clean_data`. +- If `feature_name_column` is `NA`, assigns sequential numbers +(1, 2, 3, etc.) + as feature names and issues a message.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/add_plot_to_html.html b/docs/reference/add_plot_to_html.html new file mode 100644 index 0000000..7c4bf92 --- /dev/null +++ b/docs/reference/add_plot_to_html.html @@ -0,0 +1,119 @@ + +Add Plot to HTML Content — add_plot_to_html • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Add Plot to HTML Content

    + + +
    + +
    +

    This function converts a plot to a base64 image and adds it to the +HTML content.

    +
    + +
    + 
    add_plot_to_html(html_content, plot_element, plots_size, section_index)
    +
    + +
    +

    Arguments

    + + +
    html_content
    +

    The current HTML content as a character string.

    + + +
    plot_element
    +

    The plot element to be converted to base64.

    + + +
    plots_size
    +

    An integer specifying the height of the plot.

    + + +
    section_index
    +

    An integer specifying the section index.

    + +
    +
    +

    Value

    +

    The updated HTML content as a character string.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/ask_user.html b/docs/reference/ask_user.html new file mode 100644 index 0000000..bd51e69 --- /dev/null +++ b/docs/reference/ask_user.html @@ -0,0 +1,109 @@ + +Prompt the user with a yes/no question — ask_user • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Prompt the user with a yes/no question

    + + +
    + +
    +

    This function prompts the user with a yes/no question. If the user answers +"yes" (case insensitive), the code proceeds. If the user answers "no" or +anything else, the code stops.

    +
    + +
    + 
    ask_user(question)
    +
    + +
    +

    Arguments

    + + +
    question
    +

    A string of the question to ask the user.

    + +
    +
    +

    Value

    +

    None.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/between_level.html b/docs/reference/between_level.html new file mode 100644 index 0000000..bf49ec1 --- /dev/null +++ b/docs/reference/between_level.html @@ -0,0 +1,161 @@ + +Between Level Analysis — between_level • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Between Level Analysis

    + + +
    + +
    +

    Performs a between-level analysis using LIMMA to compare specified levels +within a condition.

    +
    + +
    + 
    between_level(
+  data,
+  preprocess_rna_seq,
+  normalization_fun,
+  meta,
+  design,
+  spline_params,
+  condition,
+  compared_levels,
+  padjust_method,
+  feature_names
+)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A matrix of data values.

    + + +
    preprocess_rna_seq
    +

    Boolean specifying whether to preprocess RNA seq

    + + +
    normalization_fun
    +

    Function for normalizing RNA-seq raw-counts.

    + + +
    meta
    +

    A dataframe containing metadata, including a 'Time' column.

    + + +
    design
    +

    A design formula or matrix for the LIMMA analysis.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    compared_levels
    +

    A vector of levels within the condition to compare.

    + + +
    padjust_method
    +

    A character string specifying the p-adjustment method.

    + + +
    feature_names
    +

    A non-empty character vector of feature names.

    + +
    +
    +

    Value

    +

    A list containing top tables for the factor only and factor-time +contrast.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/bind_data_with_annotation.html b/docs/reference/bind_data_with_annotation.html new file mode 100644 index 0000000..e1d15c2 --- /dev/null +++ b/docs/reference/bind_data_with_annotation.html @@ -0,0 +1,115 @@ + +Bind Data with Annotation — bind_data_with_annotation • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Bind Data with Annotation

    + + +
    + +
    +

    This function converts a matrix to a dataframe, adds row names as the first +column, +and binds it with annotation data.

    +
    + +
    + 
    bind_data_with_annotation(data, annotation)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A matrix containing the numeric data.

    + + +
    annotation
    +

    A dataframe containing the annotation information.

    + +
    +
    +

    Value

    +

    A dataframe with `data` and `annotation` combined, and the row names + of `data` +as the first column named `feature_names`.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/build_cluster_hits_report.html b/docs/reference/build_cluster_hits_report.html new file mode 100644 index 0000000..336e7a3 --- /dev/null +++ b/docs/reference/build_cluster_hits_report.html @@ -0,0 +1,156 @@ + +Build Cluster Hits Report — build_cluster_hits_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Build Cluster Hits Report

    + + +
    + +
    +

    Generates an HTML report for clustered hits, including plots and +spline parameter details, with a table of contents.

    +
    + +
    + 
    build_cluster_hits_report(
+  header_section,
+  plots,
+  plots_sizes,
+  level_headers_info,
+  spline_params,
+  adj_pthresholds,
+  mode,
+  report_info,
+  output_file_path
+)
    +
    + +
    +

    Arguments

    + + +
    header_section
    +

    A character string containing the HTML header section.

    + + +
    plots
    +

    A list of ggplot2 plot objects.

    + + +
    plots_sizes
    +

    A list of integers specifying the size of each plot.

    + + +
    level_headers_info
    +

    A list of header information for each level.

    + + +
    spline_params
    +

    A list of spline parameters.

    + + +
    adj_pthresholds
    +

    Float vector with values for any level for adj.p.tresh

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + + +
    report_info
    +

    A named list containg the report info fields. Here used +for the email hotkey functionality.

    + + +
    output_file_path
    +

    A character string specifying the path to save the +HTML report.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/build_create_gsea_report.html b/docs/reference/build_create_gsea_report.html new file mode 100644 index 0000000..e22c86c --- /dev/null +++ b/docs/reference/build_create_gsea_report.html @@ -0,0 +1,151 @@ + +Build GSEA Report — build_create_gsea_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Build GSEA Report

    + + +
    + +
    +

    Generates an HTML report for Gene Set Enrichment Analysis (GSEA) based on +provided plot data, header information, and other content. The report +includes sections for each level of clustered hits, along with a table of +contents and various plots.

    +
    + +
    + 
    build_create_gsea_report(
+  header_section,
+  plots,
+  plots_sizes,
+  level_headers_info,
+  report_info,
+  output_file_path
+)
    +
    + +
    +

    Arguments

    + + +
    header_section
    +

    A string containing the HTML content for the header +section of the report.

    + + +
    plots
    +

    A list of plots to be included in the report.

    + + +
    plots_sizes
    +

    A list of sizes for the plots.

    + + +
    level_headers_info
    +

    A list containing header information for each +level of clustered hits.

    + + +
    report_info
    +

    A named list containg the report info fields. Here used +for the email hotkey functionality.

    + + +
    output_file_path
    +

    A string specifying the file path where the report +will be saved.

    + +
    +
    +

    Value

    +

    None. The function generates and writes an HTML report to the +specified output file path.

    +
    +
    +

    Details

    +

    The function first initializes the HTML content with the provided header +section and a placeholder for the table of contents (TOC). It then iterates +through the plots, generating sections for each level of clustered hits and +processing individual plots. The TOC is inserted into the HTML content, +which is then finalized and written to the specified output file.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/build_create_limma_report.html b/docs/reference/build_create_limma_report.html new file mode 100644 index 0000000..943a0ef --- /dev/null +++ b/docs/reference/build_create_limma_report.html @@ -0,0 +1,140 @@ + +Build Cluster Hits Report — build_create_limma_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Build Cluster Hits Report

    + + +
    + +
    +

    Generates an HTML report for clustered hits, including plots and +spline parameter details, with a table of contents.

    +
    + +
    + 
    build_create_limma_report(
+  header_section,
+  plots,
+  plots_sizes,
+  level_headers_info,
+  report_info,
+  output_file_path = here::here()
+)
    +
    + +
    +

    Arguments

    + + +
    header_section
    +

    A character string containing the HTML header section.

    + + +
    plots
    +

    A list of ggplot2 plot objects.

    + + +
    plots_sizes
    +

    A list of integers specifying the size of each plot.

    + + +
    level_headers_info
    +

    A list of header information for each level.

    + + +
    report_info
    +

    A named list containg the report info fields. Here used +for the email hotkey functionality.

    + + +
    output_file_path
    +

    A character string specifying the path to save the +HTML report.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/build_explore_data_report.html b/docs/reference/build_explore_data_report.html new file mode 100644 index 0000000..19b307f --- /dev/null +++ b/docs/reference/build_explore_data_report.html @@ -0,0 +1,136 @@ + +Build Explore Data Report — build_explore_data_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Build Explore Data Report

    + + +
    + +
    +

    This function generates an HTML report containing a header section, table of +contents, and a series of plots. Each plot is included in the report with +specified sizes.

    +
    + +
    + 
    build_explore_data_report(
+  header_section,
+  plots,
+  plots_sizes,
+  report_info,
+  output_file_path
+)
    +
    + +
    +

    Arguments

    + + +
    header_section
    +

    A string containing the HTML content for the header +section of the report.

    + + +
    plots
    +

    A list of ggplot objects representing the plots to be included +in the report.

    + + +
    plots_sizes
    +

    A list of sizes corresponding to each plot, defining the +dimensions to be used when rendering the plots.

    + + +
    report_info
    +

    A named list containg the report info fields. Here used +for the email hotkey functionality.

    + + +
    output_file_path
    +

    A string specifying the file path where the HTML +report will be saved.

    + +
    +
    +

    Value

    +

    None. This function writes the HTML content to the specified file.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/build_hyperparams_screen_report.html b/docs/reference/build_hyperparams_screen_report.html new file mode 100644 index 0000000..7d3b198 --- /dev/null +++ b/docs/reference/build_hyperparams_screen_report.html @@ -0,0 +1,136 @@ + +Build Hyperparameters Screening Report — build_hyperparams_screen_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Build Hyperparameters Screening Report

    + + +
    + +
    +

    Constructs an HTML report for hyperparameter screening by embedding plots +and their respective sizes into the provided header section.

    +
    + +
    + 
    build_hyperparams_screen_report(
+  header_section,
+  plots,
+  plots_sizes,
+  report_info,
+  output_file_path
+)
    +
    + +
    +

    Arguments

    + + +
    header_section
    +

    A character string containing the HTML header section.

    + + +
    plots
    +

    A list of ggplot2 plot objects.

    + + +
    plots_sizes
    +

    A list of integers specifying the number of rows for each +plot.

    + + +
    report_info
    +

    A named list containg the report info fields. Here used +for the email hotkey functionality.

    + + +
    output_file_path
    +

    A character string specifying the path to save the +HTML report.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    +
    +

    See also

    +

    plot2base64

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_between_level_pattern.html b/docs/reference/check_between_level_pattern.html new file mode 100644 index 0000000..492c0cc --- /dev/null +++ b/docs/reference/check_between_level_pattern.html @@ -0,0 +1,126 @@ + +Check for Between-Level Patterns in Top Tables — check_between_level_pattern • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check for Between-Level Patterns in Top Tables

    + + +
    + +
    +

    This function checks if any of the elements within a list of top tables +contain element names that match the specified between-level pattern.

    +
    + +
    + 
    check_between_level_pattern(top_tables)
    +
    + +
    +

    Arguments

    + + +
    top_tables
    +

    A list where each element is itself a list containing +named elements.

    + +
    +
    +

    Value

    +

    A list with two elements:

    between_levels
    +

    A logical value indicating whether any element names + match the between-level pattern.

    + +
    index_with_pattern
    +

    The index of the first element in `top_tables` + where all names match the between-level pattern, or NA if no match is + found.

    + + +
    +
    +

    Details

    +

    The function iterates over each element in `top_tables`. For each element +that +is a list, it checks if all names within that inner list match the pattern +`".+_vs_.+"`. If a match is found, the function sets `between_levels` to TRUE +and records the index of the matching element. The search stops at the first +match.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_clustered_hits.html b/docs/reference/check_clustered_hits.html new file mode 100644 index 0000000..73216e3 --- /dev/null +++ b/docs/reference/check_clustered_hits.html @@ -0,0 +1,115 @@ + +Check Clustered Genes Dataframe for Required Conditions — check_clustered_hits • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check Clustered Genes Dataframe for Required Conditions

    + + +
    + +
    +

    This function checks if a given dataframe `clustered_genes` contains the +required columns `gene` and `cluster`. The `gene` column must contain only +character strings of length 1, and the `cluster` column must contain only +integers. If any condition is not met, the function stops the script and +produces an informative error message.

    +
    + +
    + 
    check_clustered_hits(levels_clustered_hits)
    +
    + +
    +

    Arguments

    + + +
    levels_clustered_hits
    +

    A list of dataframes to be checked for the +required format.

    + +
    +
    +

    Value

    +

    This function does not return a value. It stops with an error message + if the conditions are not met.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_databases.html b/docs/reference/check_databases.html new file mode 100644 index 0000000..005c6db --- /dev/null +++ b/docs/reference/check_databases.html @@ -0,0 +1,110 @@ + +Check Valid Databases Dataframe — check_databases • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check Valid Databases Dataframe

    + + +
    + +
    +

    This function checks if the dataframe has exactly three columns +named DB, Geneset, and Gene, and all columns must be of type +character.

    +
    + +
    + 
    check_databases(databases)
    +
    + +
    +

    Arguments

    + + +
    databases
    +

    A dataframe to check.

    + +
    +
    +

    Value

    +

    None. This function stops execution and provides an + error message if the dataframe is not valid.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_genes.html b/docs/reference/check_genes.html new file mode 100644 index 0000000..549bf86 --- /dev/null +++ b/docs/reference/check_genes.html @@ -0,0 +1,116 @@ + +Check Valid Gene IDs — check_genes • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check Valid Gene IDs

    + + +
    + +
    +

    This function checks whether a character vector `genes` +contains only valid gene IDs. Each gene ID must consist +solely of alphabetic letters and numbers.

    +
    + +
    + 
    check_genes(genes, max_index_overall = NA)
    +
    + +
    +

    Arguments

    + + +
    genes
    +

    A character vector containing gene IDs.

    + + +
    max_index_overall
    +

    An integer, specifying the highest index of all +features across all levels.

    + +
    +
    +

    Value

    +

    None. This function stops execution and provides +an error message if the vector does not meet the criteria, +including the first offending element and its index.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_null_elements.html b/docs/reference/check_null_elements.html new file mode 100644 index 0000000..099114a --- /dev/null +++ b/docs/reference/check_null_elements.html @@ -0,0 +1,112 @@ + +Check for NULL Elements in Arguments — check_null_elements • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check for NULL Elements in Arguments

    + + +
    + +
    +

    This function checks if any elements in the provided list of arguments +are `NULL`. +If any `NULL` elements are found, it stops the execution and returns +an informative error message.

    +
    + +
    + 
    check_null_elements(args)
    +
    + +
    +

    Arguments

    + + +
    args
    +

    A list of arguments to check for `NULL` elements.

    + +
    +
    +

    Value

    +

    This function does not return a value. It stops execution if +any `NULL` elements are found in the input list.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_params.html b/docs/reference/check_params.html new file mode 100644 index 0000000..998d3f3 --- /dev/null +++ b/docs/reference/check_params.html @@ -0,0 +1,120 @@ + +Check Params List for Required Conditions — check_params • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check Params List for Required Conditions

    + + +
    + +
    +

    This function checks if a given list `params` contains only the allowed +named elements. The elements do not have to be present, but if they are, +they must be +named exactly as specified and must contain the correct data types: float, +character, int, +int, and float. If any condition is not met, the function stops the script +and produces an +informative error message. `params` can also be `NA`.

    +
    + +
    + 
    check_params(params)
    +
    + +
    +

    Arguments

    + + +
    params
    +

    A list to be checked for the required conditions, or `NA`.

    + +
    +
    +

    Value

    +

    This function does not return a value. It stops with an error message + if the conditions are not met.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/check_splineomics_elements.html b/docs/reference/check_splineomics_elements.html new file mode 100644 index 0000000..dc210a5 --- /dev/null +++ b/docs/reference/check_splineomics_elements.html @@ -0,0 +1,114 @@ + +Check for Required Elements in the SplineOmics Object — check_splineomics_elements • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check for Required Elements in the SplineOmics Object

    + + +
    + +
    +

    This function checks if the given object contains all the required named +elements for a specified function type. If any element is missing, it stops +the script and provides an informative error message.

    +
    + +
    + 
    check_splineomics_elements(splineomics, func_type)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    The object to be checked.

    + + +
    func_type
    +

    A string specifying the function type. It can be one of +"cluster_hits", "create_limma_report", "run_limma_splines", or "explore_data"

    + +
    +
    +

    Value

    +

    None. Stops execution if any required element is missing.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/clean_gene_symbols.html b/docs/reference/clean_gene_symbols.html new file mode 100644 index 0000000..73ce0c8 --- /dev/null +++ b/docs/reference/clean_gene_symbols.html @@ -0,0 +1,113 @@ + +Clean the Gene Symbols — clean_gene_symbols • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Clean the Gene Symbols

    + + +
    + +
    +

    This function preprocesses a vector of gene names by cleaning and +formatting them. It removes any non-alphanumeric characters after the +first block of alphanumeric characters and converts the remaining +characters to uppercase.

    +
    + +
    + 
    clean_gene_symbols(genes)
    +
    + +
    +

    Arguments

    + + +
    genes
    +

    A character vector containing gene names to be cleaned.

    + +
    +
    +

    Value

    +

    A character vector of cleaned gene symbols (names) with the same +length as the input. The cleaned names will be in uppercase, and any +invalid or empty gene names will be replaced with NA.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/cluster_hits.html b/docs/reference/cluster_hits.html new file mode 100644 index 0000000..5bf9073 --- /dev/null +++ b/docs/reference/cluster_hits.html @@ -0,0 +1,201 @@ + +cluster_hits.R contains the exported package function cluster_hits and all the functions that make up the functionality of cluster_hits. cluster_hits clusters the hits of a time series omics datasets (the features that were significantly changed over the time course) with hierarchical clustering of the spline shape. Cluster Hits from Top Tables — cluster_hits • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    cluster_hits.R contains the exported package function cluster_hits and all the functions that make up the functionality of cluster_hits. cluster_hits clusters the hits of a time series omics datasets (the features that were significantly changed over the time course) with hierarchical clustering of the spline shape. Cluster Hits from Top Tables

    + + +
    + +
    +

    Performs clustering on hits from top tables generated by differential +expression analysis. +This function filters hits based on adjusted p-value thresholds, extracts +spline coefficients for +significant features, normalizes these coefficients, and applies hierarchical +clustering. The results, +including clustering assignments and normalized spline curves, are saved in a +specified directory and +compiled into an HTML report.

    +
    + +
    + 
    cluster_hits(
+  splineomics,
+  genes,
+  adj_pthresholds = c(0.05),
+  clusters = c("auto"),
+  plot_info = list(y_axis_label = "Value", time_unit = "min", treatment_labels = NA,
+    treatment_timepoints = NA),
+  report_dir = here::here(),
+  analysis_type = "time_effect",
+  report = TRUE
+)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    An S3 object of class `SplineOmics` that contains all the +necessary data and parameters for the analysis, including:

    • data: The original expression dataset used for differential + expression analysis.

      • +

    • meta: A dataframe containing metadata corresponding to the + data, must include a 'Time' column and any columns specified by + conditions.

      • +

    • design: A character of length 1 representing the limma + design formula.

      • +

    • condition: Character of length 1 specifying the column name + in meta used to define groups for analysis.

      • +

    • spline_params: A list of spline parameters for the analysis.

      • +

    • meta_batch_column: A character string specifying the column + name in the metadata used for batch effect removal.

      • +

    • meta_batch2_column: A character string specifying the second + column name in the metadata used for batch effect removal.

      • +

    • limma_splines_result: A list of data frames, each representing + a top table from differential expression analysis, containing at least + 'adj.P.Val' and expression data columns.

      • +
    + + +
    genes
    +

    A character vector containing the gene names of the features to +be analyzed.

    + + +
    adj_pthresholds
    +

    Numeric vector of p-value thresholds for filtering +hits in each top table.

    + + +
    clusters
    +

    Character or integer vector specifying the number of clusters +or 'auto' for automatic estimation.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + + +
    report_dir
    +

    Character string specifying the directory path where the +HTML report and any other output files should be saved.

    + + +
    analysis_type
    +

    String specifying type of limma results (which of the +three categories: time_effect, avrg_diff_conditions, +and interaction_condition_time ( +see limma_result_categories.pdf in inst/descriptions).

    + + +
    report
    +

    Boolean TRUE or FALSE value specifing if a report should be +generated.

    + +
    +
    +

    Value

    +

    A list where each element corresponds to a group factor and contains +the clustering results, + including `clustered_hits` data frame, hierarchical clustering object + `hc`, `curve_values` + data frame with normalized spline curves, and `top_table` with + cluster assignments.

    +
    +
    +

    See also

    +

    topTable, hclust

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/control_inputs_create_gsea_report.html b/docs/reference/control_inputs_create_gsea_report.html new file mode 100644 index 0000000..507b16f --- /dev/null +++ b/docs/reference/control_inputs_create_gsea_report.html @@ -0,0 +1,127 @@ + +Control Inputs for GSEA Report — control_inputs_create_gsea_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Control Inputs for GSEA Report

    + + +
    + +
    +

    Validates the inputs for generating a GSEA report, including clustered +hits, genes, databases, parameters, plot titles, and background genes.

    +
    + +
    + 
    control_inputs_create_gsea_report(
+  levels_clustered_hits,
+  databases,
+  params,
+  plot_titles,
+  background
+)
    +
    + +
    +

    Arguments

    + + +
    levels_clustered_hits
    +

    A list containing clustered hits at various +levels.

    + + +
    databases
    +

    A list of databases to be used in the GSEA analysis.

    + + +
    params
    +

    A list of parameters for the GSEA analysis.

    + + +
    plot_titles
    +

    A character vector of titles for the plots, with length +matching `levels_clustered_hits`.

    + + +
    background
    +

    A character vector of background genes or NULL.

    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/control_inputs_extract_data.html b/docs/reference/control_inputs_extract_data.html new file mode 100644 index 0000000..437aa29 --- /dev/null +++ b/docs/reference/control_inputs_extract_data.html @@ -0,0 +1,123 @@ + +Control Inputs for Extracting Data — control_inputs_extract_data • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Control Inputs for Extracting Data

    + + +
    + +
    +

    This function checks the validity of input data and the feature name column. +It ensures that the input data is a dataframe, the feature name column is +specified correctly, and contains valid data.

    +
    + +
    + 
    control_inputs_extract_data(data, feature_name_columns)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A dataframe containing the input data.

    + + +
    feature_name_columns
    +

    A character vector specifying the names of the +feature name columns. The columns must be present +in the dataframe data. If `NA`, no column is +checked.

    + +
    +
    +

    Details

    +

    The function performs the following checks: +- Ensures the input data is a dataframe. +- Checks if the feature name column is a single string and exists in the +data. +- Ensures the specified feature name column does not contain only `NA` +values. +- Checks if the input dataframe is not empty.

    +

    If any of these checks fail, the function stops with an error message.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_enrichr_zip.html b/docs/reference/create_enrichr_zip.html new file mode 100644 index 0000000..c13cbc1 --- /dev/null +++ b/docs/reference/create_enrichr_zip.html @@ -0,0 +1,118 @@ + +Create a ZIP File for Enrichr Gene Lists — create_enrichr_zip • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create a ZIP File for Enrichr Gene Lists

    + + +
    + +
    +

    This function creates a ZIP file containing directories for each level of +gene lists. Each directory contains text files for each cluster. The ZIP file +is then encoded to base64 for easy download.

    +
    + +
    + 
    create_enrichr_zip(enrichr_format)
    +
    + +
    +

    Arguments

    + + +
    enrichr_format
    +

    A list with the formatted gene lists and background +gene list, typically the output of `prepare_gene_lists_for_enrichr`.

    + +
    +
    +

    Value

    +

    A base64-encoded string representing the ZIP file.

    +
    +
    +

    Details

    +

    The function creates a temporary directory to store the files. For each level +in the `enrichr_format$gene_lists`, it creates a directory named after the +level. Within each level directory, it creates a text file for each cluster, +containing the genes in that cluster. The directories and files are added +to a ZIP file, which is then encoded to base64.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_gsea_report_level.html b/docs/reference/create_gsea_report_level.html new file mode 100644 index 0000000..dc015af --- /dev/null +++ b/docs/reference/create_gsea_report_level.html @@ -0,0 +1,142 @@ + +Perform Gene Set Enrichment Analysis and plot it. — create_gsea_report_level • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Perform Gene Set Enrichment Analysis and plot it.

    + + +
    + +
    +

    This function conducts a Gene Set Enrichment Analysis (GSEA) using either the +clusterProfiler package. Afterwards, it plots the results. +It allows for customization of enrichment parameters, selection of databases, +and optionally specifying a custom plot title and background gene list.

    +
    + +
    + 
    create_gsea_report_level(
+  clustered_genes,
+  databases,
+  params = NA,
+  plot_title = "",
+  background = NULL
+)
    +
    + +
    +

    Arguments

    + + +
    clustered_genes
    +

    A list of dataframes with two columns: the first +column contains the standard gene symbol, and the second column contains an +integer specifying the cluster.

    + + +
    databases
    +

    A dataframe containing the data of the downloaded Enrichr +databases

    + + +
    params
    +

    A list specifying the clusterProfiler parameters for the +enrichment analysis.

    + + +
    plot_title
    +

    An optional string specifying the title of the plot. If not +provided, a default title based on the analysis will be used.

    + + +
    background
    +

    An optional list of standard gene symbols to be used as the +background for the enrichment analysis instead of the background chosen by +the `enricher`. The default is an empty list, which implies the use of the +default background set by the enrichment tool.

    + +
    +
    +

    Value

    +

    An object containing the results of the Gene Set Enrichment Analysis, +including any plots generated during the analysis.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_limma_report.html b/docs/reference/create_limma_report.html new file mode 100644 index 0000000..2b02427 --- /dev/null +++ b/docs/reference/create_limma_report.html @@ -0,0 +1,138 @@ + +Create a limma report — create_limma_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create a limma report

    + + +
    + +
    +

    Generates an HTML report based on the results of a limma analysis with +splines. +The report includes various plots and sections summarizing the analysis +results for time effects, average differences between conditions, +and interaction effects between condition and time.

    +
    + +
    + 
    create_limma_report(splineomics, adj_pthresh = 0.05, report_dir = here::here())
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    An S3 object of class `SplineOmics` that contains all the +necessary data and parameters for the analysis, including:

    • limma_splines_result: A list containing top tables from + differential expression analysis for the three different limma results.

      • +

    • meta: A data frame with sample metadata. Must contain a column + "Time".

      • +

    • condition: A character string specifying the column name in + the metadata (meta) that defines groups + for analysis. This column contains levels such as + "exponential" and "stationary" for phases, or + "drug" and "no_drug" for treatments.

      • +

    • annotation: A data frame containing feature information, + such as gene and protein names, associated with + the expression data.

      • +

    • report_info: A list containing metadata about the analysis + for reporting purposes.

      • +
    + + +
    adj_pthresh
    +

    A numeric value specifying the adjusted p-value threshold +for significance. Default is 0.05. Must be > 0 and < 1.

    + + +
    report_dir
    +

    A string specifying the directory where the report should +be saved. Default is the current working directory.

    + +
    +
    +

    Value

    +

    A list of plots included in the generated HTML report.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_p_value_histogram.html b/docs/reference/create_p_value_histogram.html new file mode 100644 index 0000000..2957325 --- /dev/null +++ b/docs/reference/create_p_value_histogram.html @@ -0,0 +1,121 @@ + +Create a p-value histogram from a limma top_table — create_p_value_histogram • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create a p-value histogram from a limma top_table

    + + +
    + +
    +

    This function generates a histogram of the unadjusted p-values from a +limma top_table.

    +
    + +
    + 
    create_p_value_histogram(
+  top_table,
+  adj_pthresh = 0.05,
+  title = "P-Value Histogram"
+)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A data frame containing the limma top_table with +a column named `P.Value` for unadjusted p-values.

    + + +
    adj_pthresh
    +

    A numeric value for the adjusted p-value threshold +(not used in this function, included for consistency).

    + + +
    title
    +

    A character string for the title of the histogram.

    + +
    +
    +

    Value

    +

    A ggplot2 object representing the histogram of unadjusted p-values.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_progress_bar.html b/docs/reference/create_progress_bar.html new file mode 100644 index 0000000..c77ac1d --- /dev/null +++ b/docs/reference/create_progress_bar.html @@ -0,0 +1,115 @@ + +utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. Create Progress Bar — create_progress_bar • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. Create Progress Bar

    + + +
    + +
    +

    Creates a progress bar for tracking the progress of an iterable task.

    +
    + +
    + 
    create_progress_bar(iterable, message = "Processing")
    +
    + +
    +

    Arguments

    + + +
    iterable
    +

    An iterable object (e.g., list or vector) whose length +determines the total number of steps.

    + + +
    message
    +

    A message to display with the progress bar +(default is "Processing").

    + +
    +
    +

    Value

    +

    A progress bar object from the 'progress' package.

    +
    +
    +

    See also

    +

    progress_bar

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_spline_params.html b/docs/reference/create_spline_params.html new file mode 100644 index 0000000..dd48fdc --- /dev/null +++ b/docs/reference/create_spline_params.html @@ -0,0 +1,127 @@ + +Create Spline Parameters — create_spline_params • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create Spline Parameters

    + + +
    + +
    +

    Generates spline parameters based on the configuration, metadata, condition, +and mode.

    +
    + +
    + 
    create_spline_params(spline_test_configs, index, meta, condition, mode)
    +
    + +
    +

    Arguments

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    index
    +

    Index of the spline configuration to process.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    mode
    +

    A character string specifying the mode.

    + +
    +
    +

    Value

    +

    A list of processed spline parameters.

    +
    +
    +

    See also

    +

    process_config_column

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_splineomics.html b/docs/reference/create_splineomics.html new file mode 100644 index 0000000..b60cd54 --- /dev/null +++ b/docs/reference/create_splineomics.html @@ -0,0 +1,203 @@ + +Create and update the SplineOmics object ===== — create_splineomics • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create and update the SplineOmics object =====

    + + +
    + +
    +

    Creates a SplineOmics object containing variables that are commonly used +across multiple functions in the package.

    +
    + +
    + 
    create_splineomics(
+  data,
+  meta,
+  condition,
+  annotation = NULL,
+  report_info = NULL,
+  meta_batch_column = NULL,
+  meta_batch2_column = NULL,
+  feature_name_columns = NULL,
+  design = NULL,
+  spline_params = NULL,
+  preprocess_rna_seq = FALSE,
+  normalization_fun = NULL,
+  padjust_method = "BH"
+)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    The actual omics data.

    + + +
    meta
    +

    Metadata associated with the omics data.

    + + +
    condition
    +

    A condition variable.

    + + +
    annotation
    +

    A dataframe with the feature descriptions of data +(optional).

    + + +
    report_info
    +

    A list containing report information such as omics data +type, data description, data collection date, analyst name, contact info, +and project name (optional).

    + + +
    meta_batch_column
    +

    Column for meta batch information (optional).

    + + +
    meta_batch2_column
    +

    Column for secondary meta batch information +(optional).

    + + +
    feature_name_columns
    +

    Character vector containing the column names of +the annotation info that describe the features. +This argument is used to specify in the HTML +report how exactly the feature names displayed +above each individual spline plot have been +created. Use the same vector that was used to +create the row headers for the data matrix!

    + + +
    design
    +

    A design matrix or similar object (optional).

    + + +
    spline_params
    +

    Parameters for spline functions (optional).

    + + +
    preprocess_rna_seq
    +

    Boolean specifying whether to preprocess RNA seq

    + + +
    normalization_fun
    +

    Function used for normalizing RNA-seq. Must take as +input the y of: y <- edgeR::DGEList(counts = raw_counts) and output the y +with the normalized counts.

    + + +
    padjust_method
    +

    Method for p-value adjustment, one of "none", "BH", +"BY", "holm", "bonferroni", "hochberg", or "hommel". +Defaults to "BH" (Benjamini-Hochberg).

    + +
    +
    +

    Value

    +

    A SplineOmics object.

    +
    +
    +

    Details

    +

    Description +———– +Contains the functions to create and update a SplineOmics object. This object +is used to collect function arguments, that are equivalent for more than one +exported function of the SplineOmics package. Additionally

    +

    Functions +——— +- create_splineomics: Create a SplineOmics object +- update_splineomics: Add additional arguments to the SplineOmics +object or overwrite existing arguments.

    +

    Classes +——- +None

    +

    Notes +—– +None +Create a SplineOmics object

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_toc.html b/docs/reference/create_toc.html new file mode 100644 index 0000000..d050c40 --- /dev/null +++ b/docs/reference/create_toc.html @@ -0,0 +1,97 @@ + +Create Table of Contents — create_toc • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create Table of Contents

    + + +
    + +
    +

    Creates the HTML content for the Table of Contents.

    +
    + +
    + 
    create_toc()
    +
    + +
    +

    Value

    +

    A string containing the HTML for the Table of Contents.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/create_volcano_plot.html b/docs/reference/create_volcano_plot.html new file mode 100644 index 0000000..0190628 --- /dev/null +++ b/docs/reference/create_volcano_plot.html @@ -0,0 +1,117 @@ + +Create a Volcano Plot — create_volcano_plot • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create a Volcano Plot

    + + +
    + +
    +

    This function creates a volcano plot from a limma top table, plotting +log fold changes against the negative log10 of adjusted p-values.

    +
    + +
    + 
    create_volcano_plot(top_table, adj_pthresh, compared_levels)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A data frame from limma containing 'logFC' and 'adj.P.Val' +columns.

    + + +
    adj_pthresh
    +

    A numeric value for the adjusted p-value threshold.

    + + +
    compared_levels
    +

    A character vector of length 2 specifying the +compared levels.

    + +
    +
    +

    Value

    +

    A ggplot object representing the volcano plot.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/dbs_to_term2genes.html b/docs/reference/dbs_to_term2genes.html new file mode 100644 index 0000000..7e65e22 --- /dev/null +++ b/docs/reference/dbs_to_term2genes.html @@ -0,0 +1,121 @@ + +Convert Database File to TERM2GENE List — dbs_to_term2genes • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Convert Database File to TERM2GENE List

    + + +
    + +
    +

    Reads a specified .tsv file containing information about databases, +gene sets, and genes. The file should have three columns: 'DB' for database +names, Geneset' for gene set identifiers, and 'Gene' for gene names. This +function organizes this information into a nested list. Each top-level +element corresponds to a unique database, and within each, gene sets map to +lists of associated genes.

    +
    + +
    + 
    dbs_to_term2genes(databases)
    +
    + +
    +

    Arguments

    + + +
    databases
    +

    A dataframe, containing the three columns DB, Geneset, and +gene. This dataframe contains the databases downloaded from +Enrichr with the SplineOmics package function: +download_enrichr_databases.

    + +
    +
    +

    Value

    +

    A nested list where the first level of names corresponds to database +names ('DB'), + the second level to gene sets ('Geneset'), and the innermost lists + contain gene names ('Gene') associated with each gene set.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/define_html_styles.html b/docs/reference/define_html_styles.html new file mode 100644 index 0000000..e7f4836 --- /dev/null +++ b/docs/reference/define_html_styles.html @@ -0,0 +1,99 @@ + +Define HTML Styles — define_html_styles • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Define HTML Styles

    + + +
    + +
    +

    Defines the CSS styles for section headers and Table of Contents (TOC) +entries used in the GSEA report generation.

    +
    + +
    + 
    define_html_styles()
    +
    + +
    +

    Value

    +

    A list containing the styles for section headers and TOC entries.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/design2design_matrix.html b/docs/reference/design2design_matrix.html new file mode 100644 index 0000000..0f3e72b --- /dev/null +++ b/docs/reference/design2design_matrix.html @@ -0,0 +1,126 @@ + +Create Design Matrix for Splines — design2design_matrix • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create Design Matrix for Splines

    + + +
    + +
    +

    This function generates a design matrix using spline parameters and metadata. +It accommodates both B-splines and natural cubic splines based on the provided +spline type and parameters.

    +
    + +
    + 
    design2design_matrix(meta, spline_params, level_index, design)
    +
    + +
    +

    Arguments

    + + +
    meta
    +

    A dataframe containing the metadata, including the time column.

    + + +
    spline_params
    +

    A list containing the spline parameters. This list can +include `dof` (degrees of freedom), `knots`, `bknots` (boundary knots), +`spline_type`, and `degree`.

    + + +
    level_index
    +

    An integer representing the current level index for which +the design matrix is being generated.

    + + +
    design
    +

    A character string representing the design formula to be used +for generating the model matrix.

    + +
    +
    +

    Value

    +

    A design matrix constructed using the specified spline parameters and +design formula.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/determine_analysis_mode.html b/docs/reference/determine_analysis_mode.html new file mode 100644 index 0000000..5d816de --- /dev/null +++ b/docs/reference/determine_analysis_mode.html @@ -0,0 +1,119 @@ + +Determine Analysis Mode Based on Design Formula — determine_analysis_mode • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Determine Analysis Mode Based on Design Formula

    + + +
    + +
    +

    This function determines whether each level should be analyzed in isolation +or together based on the design formula. If the design formula includes +interaction terms involving the factor of the experiment, the analysis +mode is considered integrated (together). Otherwise, it is considered isolated.

    +
    + +
    + 
    determine_analysis_mode(design, factor_column)
    +
    + +
    +

    Arguments

    + + +
    design
    +

    A character string representing the design formula to be used +for generating the model matrix.

    + + +
    factor_column
    +

    A character string representing the column name of the +factor of the experiment in the metadata.

    + +
    +
    +

    Value

    +

    A character string indicating the analysis mode, either "integrated" +if the design formula involves interaction terms with the factor of the +experiment, or "isolated" otherwise.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/download_enrichr_databases.html b/docs/reference/download_enrichr_databases.html new file mode 100644 index 0000000..4121423 --- /dev/null +++ b/docs/reference/download_enrichr_databases.html @@ -0,0 +1,118 @@ + +The exported function download_enrichr_databases allows to selects & download Enrichr databases for local use with clusterProfiler. Download Enrichr Databases — download_enrichr_databases • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    The exported function download_enrichr_databases allows to selects & download Enrichr databases for local use with clusterProfiler. Download Enrichr Databases

    + + +
    + +
    +

    This function downloads gene sets from specified Enrichr databases and saves + them to a specified output directory as a .tsv file. The file is named with + a timestamp to ensure uniqueness.

    +
    + +
    + 
    download_enrichr_databases(gene_set_lib, output_dir = here::here())
    +
    + +
    +

    Arguments

    + + +
    gene_set_lib
    +

    A character vector of database names to download from +Enrichr.

    + + +
    output_dir
    +

    A character string specifying the output directory +where the .tsv file will be saved. Defaults to the current +working directory.

    + +
    +
    +

    Value

    +

    This function does not return a value but saves a .tsv file in the + specified directory containing the gene sets from the specified + Enrichr databases.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/encode_df_to_base64.html b/docs/reference/encode_df_to_base64.html new file mode 100644 index 0000000..333d2c4 --- /dev/null +++ b/docs/reference/encode_df_to_base64.html @@ -0,0 +1,117 @@ + +Encode DataFrame to Base64 for HTML Embedding — encode_df_to_base64 • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Encode DataFrame to Base64 for HTML Embedding

    + + +
    + +
    +

    This function takes a dataframe as input and returns a base64 encoded +CSV object. The encoded object can be embedded into an HTML document +directly, with a button to download the file without pointing to a +local file.

    +
    + +
    + 
    encode_df_to_base64(df, report_type = NA)
    +
    + +
    +

    Arguments

    + + +
    df
    +

    A dataframe to be encoded.

    + + +
    report_type
    +

    (Optional) A string specifying for which report generation +this function is called. Generates different Excel sheet +names based on the report_type.

    + +
    +
    +

    Value

    +

    A character string containing the base64 encoded CSV data.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/enrichr_get_genesets.html b/docs/reference/enrichr_get_genesets.html new file mode 100644 index 0000000..5d1f4ca --- /dev/null +++ b/docs/reference/enrichr_get_genesets.html @@ -0,0 +1,112 @@ + +Get Enrichr Gene Sets — enrichr_get_genesets • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Get Enrichr Gene Sets

    + + +
    + +
    +

    This function downloads gene sets from specified Enrichr databases. +It returns a list where each element is a list corresponding to a database, +with each element containing a vector of human gene symbols for a gene set.

    +
    + +
    + 
    enrichr_get_genesets(databases)
    +
    + +
    +

    Arguments

    + + +
    databases
    +

    A character vector of database names to download from +Enrichr.

    + +
    +
    +

    Value

    +

    A named list of gene sets from the specified Enrichr databases. Each + database is represented as a list, with gene set names as list + names and vectors of human gene symbols as list elements.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/ensure_clusterProfiler.html b/docs/reference/ensure_clusterProfiler.html new file mode 100644 index 0000000..35ded19 --- /dev/null +++ b/docs/reference/ensure_clusterProfiler.html @@ -0,0 +1,99 @@ + +Ensure 'clusterProfiler' is installed and loaded — ensure_clusterProfiler • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Ensure 'clusterProfiler' is installed and loaded

    + + +
    + +
    +

    This function checks if the 'clusterProfiler' package is installed. +If not, it prompts the user to choose whether to install it automatically, +install it manually, or cancel the operation. Once installed, the package +is loaded for use.

    +
    + +
    + 
    ensure_clusterProfiler()
    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/explore_data.html b/docs/reference/explore_data.html new file mode 100644 index 0000000..37acd37 --- /dev/null +++ b/docs/reference/explore_data.html @@ -0,0 +1,122 @@ + +Generate Exploratory Plots — explore_data • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Exploratory Plots

    + + +
    + +
    +

    This function takes a data matrix, checks its validity, and generates a list +of exploratory plots including density plots, boxplots, PCA plots, MDS plots, +variance explained plots, and violin plots.

    +
    + +
    + 
    explore_data(splineomics, report_dir = here::here(), report = TRUE)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    A SplineOmics object, containing the data, meta, +condition, report_info, meta_batch_column, and +meta_batch2_column;

    + + +
    report_dir
    +

    A non-empty string specifying the report directory.

    + + +
    report
    +

    A Boolean TRUE or FALSE value, specifying if a report should +be generated or not. A report is generated per default, but +when only the plots as plot objects inside R are desired, this +argument can be set to FALSE.

    + +
    +
    +

    Value

    +

    A list of ggplot objects representing various exploratory plots.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/extract_data.html b/docs/reference/extract_data.html new file mode 100644 index 0000000..0b28505 --- /dev/null +++ b/docs/reference/extract_data.html @@ -0,0 +1,127 @@ + +extract_data.R contains the exported package function extract_data. This function automatically recognises the data field in a table and returns the data matrix, that serves as input for the other functions of this package. This is for convenience only. Extract Numeric Matrix from Dataframe — extract_data • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    extract_data.R contains the exported package function extract_data. This function automatically recognises the data field in a table and returns the data matrix, that serves as input for the other functions of this package. This is for convenience only. Extract Numeric Matrix from Dataframe

    + + +
    + +
    +

    This function takes a dataframe and identifies a rectangular or quadratic +area containing numeric data, starting from the first occurrence of a +6x6 block of numeric values. It then extracts this area into a matrix, +ensuring that each row contains only numeric values. Rows with any NA values +are removed from the resulting matrix.

    +
    + +
    + 
    extract_data(data, feature_name_columns = NA, user_prompt = TRUE)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A dataframe loaded from a tabular file, potentially containing a +rectangular or quadratic area with numeric data amidst other values.

    + + +
    feature_name_columns
    +

    (Optional) A character vector, specifying the +columns of the dataframe data, that should be +used to construct the feature names. If ommited, +the feature names are just numbers (stored as +characters) starting from 1 (1, 2, 3, etc.)

    + + +
    user_prompt
    +

    Boolean specifying whether the user prompt about the +correct format of the input data should be shown.

    + +
    +
    +

    Value

    +

    A numeric matrix with row headers and appropriate column names.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/figures/SplineOmics_graphical_abstract.png b/docs/reference/figures/SplineOmics_graphical_abstract.png new file mode 100755 index 0000000000000000000000000000000000000000..d47461cba40b86f9e7e3bec8a81c0e01c433e711 GIT binary patch literal 373029 zcmeFZby(DE_cw|g6-7cf2udpm0us`VVjzulhje$R0c=G;KtNig1O!AJx)c#5B}ZB% zhDKuOfp>jD_kKK&zxSNyy{_}exz01!2*Z5qzSq6tvp#Fx-d9$XCMKjJ#KXfQmbr0N z1rLu>1P||^>yg9oO}0(91N?g6t)}IwV(h`-=g8z0VCHFMj)&*juO2=` zT+e;v-bnm2#_ukNc@@desR&N4Hxy;|j^GcTalM4b_;uMZ5J`p3PqiKTGe`P<8<`1( z+3D(OQ@3ap9d|FDV~(onX0#&Yp$~ld#AYCh@aI`P-eK|;B3ag$H~XZ&2i1s%AMz|1R;Z% zv#Gg=%GK*XZUKLZpS5&#brj*^^6>EB^x)-maJJyOC@d_@#m&RT!@~h*aJYEcyBd3P z*t;+yx7feORWlb8XDdfnD+hZ9p6+U8{y&_K9Qo&Tx$vJOH_WUoEMYRgUZmt~Wd?FUW(>`XNqO9j?EZ z2a(bL`>+2#WHhuXg=cT>p^-{-cxst6l%!5*Oh=0ME=GP@MuPwT)2NmkneYTr za-^x*vjpcJStkxzwrfGm_mvsW=>2t!@|aPP$1HAeli))b1;Y&v_x!)a3ehcJT^!q% zecG0`#6*jQT)q!W<@Hz}+JmV7_QQzm!S#Rpa{mk4*iXX0KlIW{3iJCTby-J~@qd3P 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flatten_spline_configs • SplineOmics + + +

    +
    + + + +
    +
    +
    +

    Flatten Spline Configurations

    + + +
    + +
    +

    Flattens and formats spline configurations into a list of formatted strings.

    +
    + +
    + 
    flatten_spline_configs(spline_configs)
    +
    + +
    +

    Arguments

    + + +
    spline_configs
    +

    A list of spline configuration objects.

    + +
    +
    +

    Value

    +

    A list of formatted strings representing each spline configuration.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/format_text.html b/docs/reference/format_text.html new file mode 100644 index 0000000..b1dbb08 --- /dev/null +++ b/docs/reference/format_text.html @@ -0,0 +1,113 @@ + +Format text — format_text • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Format text

    + + +
    + +
    +

    This function takes a character vector `text` and splits it into individual +characters. It then iterates over the characters and builds lines not +exceeding +a specified character limit (default 70). Newlines are inserted between lines +using the `<br>` tag, suitable for HTML display.

    +
    + +
    + 
    format_text(text)
    +
    + +
    +

    Arguments

    + + +
    text
    +

    A character vector to be formatted.

    + +
    +
    +

    Value

    +

    A character vector with formatted text containing line breaks.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/gen_composite_spline_plots.html b/docs/reference/gen_composite_spline_plots.html new file mode 100644 index 0000000..69779d3 --- /dev/null +++ b/docs/reference/gen_composite_spline_plots.html @@ -0,0 +1,138 @@ + +Generate Composite Spline Plots — gen_composite_spline_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Composite Spline Plots

    + + +
    + +
    +

    Creates composite spline plots for significant and non-significant features +across multiple levels within a condition. +One half of one condition comparison HTML +(composite spline plots for one 'condition' inside one condition comparison)

    +
    + +
    + 
    gen_composite_spline_plots(
+  internal_combos,
+  datas,
+  metas,
+  spline_test_configs,
+  time_unit_label
+)
    +
    + +
    +

    Arguments

    + + +
    internal_combos
    +

    A list containing combinations of top tables.

    + + +
    datas
    +

    A list of matrices.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    time_unit_label
    +

    A character string specifying the time unit label +for plots.

    + +
    +
    +

    Value

    +

    A list containing the composite spline plots and their lengths.

    +
    +
    +

    See also

    +

    plot_composite_splines

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/gen_hitcomp_plots.html b/docs/reference/gen_hitcomp_plots.html new file mode 100644 index 0000000..d706cfa --- /dev/null +++ b/docs/reference/gen_hitcomp_plots.html @@ -0,0 +1,113 @@ + +Generate Hit Comparison Plots — gen_hitcomp_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Hit Comparison Plots

    + + +
    + +
    +

    Generates Venn heatmap and barplot for a given combination pair of top +tables.

    +
    + +
    + 
    gen_hitcomp_plots(combo_pair)
    +
    + +
    +

    Arguments

    + + +
    combo_pair
    +

    A list containing two combinations of top tables.

    + +
    +
    +

    Value

    +

    A list containing the Venn heatmap plot, the number of hits divided +by 16, the barplot, and a length indicator for the barplot.

    +
    +
    +

    See also

    +

    hc_new, hc_add, hc_vennheatmap, +hc_barplot

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_and_write_html.html b/docs/reference/generate_and_write_html.html new file mode 100644 index 0000000..8dbfab5 --- /dev/null +++ b/docs/reference/generate_and_write_html.html @@ -0,0 +1,120 @@ + +Generate and Write HTML Report — generate_and_write_html • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate and Write HTML Report

    + + +
    + +
    +

    This function generates an HTML report by inserting a table of contents, +embedding necessary JavaScript files, and writing the final HTML content +to a specified output file.

    +
    + +
    + 
    generate_and_write_html(toc, html_content, report_info, output_file_path)
    +
    + +
    +

    Arguments

    + + +
    toc
    +

    A string containing the table of contents in HTML format.

    + + +
    html_content
    +

    A string containing the main HTML content with a +placeholder for the table of contents.

    + + +
    report_info
    +

    A list containing report information such as +`contact_info` and `analyst_name`.

    + + +
    output_file_path
    +

    A string specifying the path where the final +HTML file will be written.

    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_avrg_diff_plots.html b/docs/reference/generate_avrg_diff_plots.html new file mode 100644 index 0000000..c7ea461 --- /dev/null +++ b/docs/reference/generate_avrg_diff_plots.html @@ -0,0 +1,116 @@ + +Generate Plots for Average Difference Conditions — generate_avrg_diff_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Plots for Average Difference Conditions

    + + +
    + +
    +

    Creates p-value histograms and volcano plots for each condition in the +average difference conditions. This function is used internally in the +`create_limma_report` function.

    +
    + +
    + 
    generate_avrg_diff_plots(avrg_diff_conditions, adj_pthresh)
    +
    + +
    +

    Arguments

    + + +
    avrg_diff_conditions
    +

    A list of top tables from the LIMMA analysis +representing the average difference between conditions.

    + + +
    adj_pthresh
    +

    A numeric value specifying the adjusted p-value threshold +for significance.

    + +
    +
    +

    Value

    +

    A list containing the plots and their sizes, as well as the +section header information.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_explore_plots.html b/docs/reference/generate_explore_plots.html new file mode 100644 index 0000000..68220a5 --- /dev/null +++ b/docs/reference/generate_explore_plots.html @@ -0,0 +1,125 @@ + +Generate exploratory plots — generate_explore_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate exploratory plots

    + + +
    + +
    +

    This function generates various exploratory plots including density plots, +box plots, violin plots, PCA plots, and correlation heatmaps based on the +provided data and metadata.

    +
    + +
    + 
    generate_explore_plots(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A data frame or matrix containing the data to be plotted.

    + + +
    meta
    +

    A data frame containing metadata associated with the data.

    + + +
    condition
    +

    A string specifying the column in the metadata that contains +the condition or grouping variable.

    + +
    +
    +

    Value

    +

    A list containing two elements:

    plots
    +

    A list of ggplot objects representing the generated plots.

    + +
    plots_sizes
    +

    A vector of numeric values indicating the sizes of the + corresponding plots.

    + + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_interaction_plots.html b/docs/reference/generate_interaction_plots.html new file mode 100644 index 0000000..94f50bd --- /dev/null +++ b/docs/reference/generate_interaction_plots.html @@ -0,0 +1,117 @@ + +Generate Plots for Interaction of Condition and Time — generate_interaction_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Plots for Interaction of Condition and Time

    + + +
    + +
    +

    Creates p-value histograms for each interaction condition in the +interaction of condition and time. This function is used internally in the +`create_limma_report` function.

    +
    + +
    + 
    generate_interaction_plots(interaction_condition_time, adj_pthresh)
    +
    + +
    +

    Arguments

    + + +
    interaction_condition_time
    +

    A list of top tables from the LIMMA +analysis +representing the interaction effects between condition and time.

    + + +
    adj_pthresh
    +

    A numeric value specifying the adjusted p-value threshold +for significance.

    + +
    +
    +

    Value

    +

    A list containing the plots and their sizes, as well as the +section header information.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_report_html.html b/docs/reference/generate_report_html.html new file mode 100644 index 0000000..5768f83 --- /dev/null +++ b/docs/reference/generate_report_html.html @@ -0,0 +1,212 @@ + +utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. The level separation is only valid internally in this script, and has no connection to the script level of the respective exported functions scripts. Generate Report HTML — generate_report_html • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. The level separation is only valid internally in this script, and has no connection to the script level of the respective exported functions scripts. Generate Report HTML

    + + +
    + +
    +

    Generates an HTML report with the provided plots, spline parameters, and +report information.

    +
    + +
    + 
    generate_report_html(
+  plots,
+  plots_sizes,
+  report_info,
+  data = NULL,
+  meta = NA,
+  topTables = NA,
+  enrichr_format = NA,
+  level_headers_info = NA,
+  spline_params = NA,
+  adj_pthresholds = NA,
+  report_type = "explore_data",
+  feature_name_columns = NA,
+  analysis_type = NA,
+  mode = NA,
+  filename = "report",
+  timestamp = format(Sys.time(), "%d_%m_%Y-%H_%M_%S"),
+  report_dir = here::here()
+)
    +
    + +
    +

    Arguments

    + + +
    plots
    +

    A list of ggplot2 plot objects.

    + + +
    plots_sizes
    +

    A list of integers specifying the size of each plot.

    + + +
    report_info
    +

    A named list containing report information.

    + + +
    data
    +

    A dataframe or a list of dataframes, containing data that should +be directly embedded in the HTML report for downloading.

    + + +
    meta
    +

    A dataframe, containing metadata that should +be directly embedded in the HTML report for downloading.

    + + +
    topTables
    +

    List of limma topTables

    + + +
    enrichr_format
    +

    List, containing two lists: The gene list and the list +of background genes.

    + + +
    level_headers_info
    +

    A list of header information for each level.

    + + +
    spline_params
    +

    A list of spline parameters, such as dof and type.

    + + +
    adj_pthresholds
    +

    Numeric vector with the values for the adj.p.tresholds +for each level.

    + + +
    report_type
    +

    A character string specifying the report type +('screen_limma_hyperparams' or 'cluster_hits').

    + + +
    feature_name_columns
    +

    Character vector with the column names of the +annotation information, such as the columns +containing the gene names. These column names +are used to put the info in the HTML reports on +how the descriptions above the individual spline +plots where created. This is because those +descriptions can be made up of several column +values, and the specific columns are then stated +in the HTML report on top (e.g gene_uniprotID).

    + + +
    analysis_type
    +

    One of the strings "time_effect", "avrg_diff_conditions" +, or "interaction_condition_time". Those represent the +three different outputs of a limma analysis. For more +info on those 3 "categories", see package dir inst/ +descriptions/limma_result_categories.pdf.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + + +
    filename
    +

    A character string specifying the filename for the report.

    + + +
    timestamp
    +

    A timestamp to include in the report filename.

    + + +
    report_dir
    +

    A character string specifying the report directory.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_reports.html b/docs/reference/generate_reports.html new file mode 100644 index 0000000..d1ace76 --- /dev/null +++ b/docs/reference/generate_reports.html @@ -0,0 +1,117 @@ + +Generate Reports — generate_reports • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Reports

    + + +
    + +
    +

    Builds HTML reports for all pairwise hyperparameter combination comparisons.

    +
    + +
    + 
    generate_reports(combo_pair_plots, report_info, report_dir, timestamp)
    +
    + +
    +

    Arguments

    + + +
    combo_pair_plots
    +

    A list of plots for each pair of combinations.

    + + +
    report_info
    +

    An object containing report information.

    + + +
    report_dir
    +

    A non-empty string specifying the report directory.

    + + +
    timestamp
    +

    A timestamp to include in the reports.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_reports_meta.html b/docs/reference/generate_reports_meta.html new file mode 100644 index 0000000..6f34a03 --- /dev/null +++ b/docs/reference/generate_reports_meta.html @@ -0,0 +1,134 @@ + +Generate Reports Metadata — generate_reports_meta • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Reports Metadata

    + + +
    + +
    +

    Generates a metadata table for the LIMMA hyperparameter screen reports and +saves it as an HTML file with custom styling.

    +
    + +
    + 
    generate_reports_meta(
+  datas_descr,
+  designs,
+  modes,
+  spline_test_configs,
+  report_dir,
+  timestamp
+)
    +
    + +
    +

    Arguments

    + + +
    datas_descr
    +

    A description object for the data.

    + + +
    designs
    +

    A list of design matrices.

    + + +
    modes
    +

    A character vector containing 'isolated' or 'integrated'.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    report_dir
    +

    A non-empty string specifying the report directory.

    + + +
    timestamp
    +

    A timestamp to include in the report filename.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_section_content.html b/docs/reference/generate_section_content.html new file mode 100644 index 0000000..a2a6d94 --- /dev/null +++ b/docs/reference/generate_section_content.html @@ -0,0 +1,134 @@ + +Generate Section Content — generate_section_content • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Section Content

    + + +
    + +
    +

    Generates the HTML content for a section, including headers and enrichment +results.

    +
    + +
    + 
    generate_section_content(
+  section_info,
+  index,
+  toc,
+  html_content,
+  section_header_style,
+  toc_style
+)
    +
    + +
    +

    Arguments

    + + +
    section_info
    +

    A list containing the information for the section.

    + + +
    index
    +

    The index of the current section.

    + + +
    toc
    +

    The current state of the Table of Contents.

    + + +
    html_content
    +

    The current state of the HTML content.

    + + +
    section_header_style
    +

    The CSS style for the section headers.

    + + +
    toc_style
    +

    The CSS style for the TOC entries.

    + +
    +
    +

    Value

    +

    A list with updated HTML content and TOC.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/generate_time_effect_plots.html b/docs/reference/generate_time_effect_plots.html new file mode 100644 index 0000000..29ec525 --- /dev/null +++ b/docs/reference/generate_time_effect_plots.html @@ -0,0 +1,114 @@ + +Generate Plots for Time Effect — generate_time_effect_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Plots for Time Effect

    + + +
    + +
    +

    Creates p-value histograms for each time effect in the LIMMA analysis. This +function is used internally in the `create_limma_report` function.

    +
    + +
    + 
    generate_time_effect_plots(time_effect, adj_pthresh)
    +
    + +
    +

    Arguments

    + + +
    time_effect
    +

    A list of top tables from the LIMMA analysis representing +the time effects.

    + + +
    adj_pthresh
    +

    A numeric value specifying the adjusted p-value threshold +for significance.

    + +
    +
    +

    Value

    +

    A list containing the plots and their sizes, as well as the +section header information.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_curve_values.html b/docs/reference/get_curve_values.html new file mode 100644 index 0000000..f06abeb --- /dev/null +++ b/docs/reference/get_curve_values.html @@ -0,0 +1,143 @@ + +Calculate Curve Values Based on Top Table Filter — get_curve_values • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Calculate Curve Values Based on Top Table Filter

    + + +
    + +
    +

    This function filters entries from a given top table based on +an adjusted p-value threshold, +performs spline interpolation using specified degrees of freedom, and +calculates curve values +for the selected entries at predefined time points. The function is +internal and not exported.

    +
    + +
    + 
    get_curve_values(top_table, level, meta, condition, spline_params, mode)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A data frame containing data with a column for adjusted +p-values and + expression averages which indicate the number of degrees + of freedom.

    + + +
    level
    +

    The specific level of the condition to filter on in the +metadata.

    + + +
    meta
    +

    Metadata containing time points and conditions.

    + + +
    condition
    +

    The name of the condition column in the metadata to filter +on.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + +
    +
    +

    Value

    +

    A list containing two elements: `curve_values`, a data frame of +curve values for each filtered entry, and `smooth_timepoints`, the time +points at which curves were evaluated.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_explore_plots_explanations.html b/docs/reference/get_explore_plots_explanations.html new file mode 100644 index 0000000..d0dfe11 --- /dev/null +++ b/docs/reference/get_explore_plots_explanations.html @@ -0,0 +1,107 @@ + +Get Plot Explanations — get_explore_plots_explanations • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Get Plot Explanations

    + + +
    + +
    +

    This function returns a vector of text explanations for various types of +plots. These explanations are used in HTML reports to describe the plots.

    +
    + +
    + 
    get_explore_plots_explanations()
    +
    + +
    +

    Value

    +

    A character vector containing explanations for different plot types.

    +
    +
    +

    Details

    +

    The explanations cover a variety of plots, including density plots, boxplots, +violin plots, mean time correlation plots, lag-1 differences plots, first lag +autocorrelation plots, coefficient of variation (CV) plots, PCA plots, PCA +variance explained plots, MDS plots, and correlation heatmaps. Each +explanation provides insights on what the plot shows and how to interpret it.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_header_section.html b/docs/reference/get_header_section.html new file mode 100644 index 0000000..f06cc3d --- /dev/null +++ b/docs/reference/get_header_section.html @@ -0,0 +1,134 @@ + +Get Header Section — get_header_section • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Get Header Section

    + + +
    + +
    +

    Generates the HTML header section for a report, including the title, header +text, and logo. This section also includes the styling for the table and +other HTML elements.

    +
    + +
    + 
    get_header_section(title, header_text, report_type, feature_names_formula)
    +
    + +
    +

    Arguments

    + + +
    title
    +

    A string specifying the title of the HTML document.

    + + +
    header_text
    +

    A string specifying the text to be displayed in the +header of the report.

    + + +
    report_type
    +

    A character specifying the type of HTML report.

    + + +
    feature_names_formula
    +

    String describing which columns of the +annotation info, such as gene and uniprotID, +where used to construct the description above +the individual spline plots. This is placed in +the beginning of the output HTML reports.

    + +
    +
    +

    Value

    +

    A string containing the HTML header section.

    +
    +
    +

    Details

    +

    The function checks the `DEVTOOLS_LOAD` environment variable to determine +the path to the logo image. The logo image is then converted to a base64 +data URI and included in the HTML. The header section includes styles for +tables, table cells, and header elements to ensure proper formatting and +alignment.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_level_hit_indices.html b/docs/reference/get_level_hit_indices.html new file mode 100644 index 0000000..c4fc5c4 --- /dev/null +++ b/docs/reference/get_level_hit_indices.html @@ -0,0 +1,127 @@ + +Get Hit Indices for a Specific Level — get_level_hit_indices • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Get Hit Indices for a Specific Level

    + + +
    + +
    +

    This function retrieves unique feature indices from a list of between-level +top tables for a specified level, based on adjusted p-value thresholds.

    +
    + +
    + 
    get_level_hit_indices(between_level_top_tables, level, adj_pthresholds)
    +
    + +
    +

    Arguments

    + + +
    between_level_top_tables
    +

    A list of data frames containing the +between-level top tables.

    + + +
    level
    +

    A string specifying the level to search for within the names +of the data frames.

    + + +
    adj_pthresholds
    +

    A numeric vector of adjusted p-value thresholds for +each data frame in `between_level_top_tables`.

    + +
    +
    +

    Value

    +

    A vector of unique feature indices that meet the adjusted p-value +threshold criteria for the specified level.

    +
    +
    +

    Details

    +

    The function iterates over each data frame in `between_level_top_tables`. For +each data frame whose name contains the specified level (case insensitive), +it identifies the rows where the adjusted p-value is below the corresponding +threshold. The function then extracts the feature indices from these rows and +compiles a unique list of these indices.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_limma_combos_results.html b/docs/reference/get_limma_combos_results.html new file mode 100644 index 0000000..ddb8f8c --- /dev/null +++ b/docs/reference/get_limma_combos_results.html @@ -0,0 +1,151 @@ + +Generate LIMMA Combination Results — get_limma_combos_results • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate LIMMA Combination Results

    + + +
    + +
    +

    Computes results for various combinations of data, design matrices, and +spline configurations using the LIMMA method.

    +
    + +
    + 
    get_limma_combos_results(
+  datas,
+  metas,
+  designs,
+  modes,
+  condition,
+  spline_test_configs,
+  feature_names,
+  adj_pthresholds,
+  padjust_method
+)
    +
    + +
    +

    Arguments

    + + +
    datas
    +

    A list of matrices.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +
    designs
    +

    A list of design matrices.

    + + +
    modes
    +

    A character vector containing 'isolated' or 'integrated'.

    + + +
    condition
    +

    A single character string specifying the condition.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    feature_names
    +

    A character vector of feature names.

    + + +
    adj_pthresholds
    +

    A numeric vector with elements > 0 and < 1.

    + + +
    padjust_method
    +

    A single character string specifying the p-adjustment +method.

    + +
    +
    +

    Value

    +

    A list of results for each combination of data, design, and spline +configuration.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/get_spline_params_info.html b/docs/reference/get_spline_params_info.html new file mode 100644 index 0000000..290bebc --- /dev/null +++ b/docs/reference/get_spline_params_info.html @@ -0,0 +1,126 @@ + +Get Spline Parameters Info — get_spline_params_info • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Get Spline Parameters Info

    + + +
    + +
    +

    This function retrieves the spline parameters information for a given index. +It ensures the spline parameters are valid and constructs an HTML string +describing the spline parameters.

    +
    + +
    + 
    get_spline_params_info(spline_params, j)
    +
    + +
    +

    Arguments

    + + +
    spline_params
    +

    A list containing the spline parameters. The list should +include elements: `spline_type`, `degree`, `dof`, +`knots`, and `bknots`.

    + + +
    j
    +

    An integer specifying the index of the spline parameters to +retrieve.

    + +
    +
    +

    Value

    +

    A character string containing HTML-formatted information about the + spline parameters at the specified index.

    +
    +
    +

    Details

    +

    The function checks if the spline parameters are not `NULL` and have a length +greater than or equal to the specified index `j`. If a parameter is +invalid or +missing, it sets the parameter to `NA`. It then constructs an HTML string +describing the spline parameters, including spline type, degree, degrees of +freedom (DoF), knots, and boundary knots.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/hc_add.html b/docs/reference/hc_add.html new file mode 100644 index 0000000..0b900e8 --- /dev/null +++ b/docs/reference/hc_add.html @@ -0,0 +1,123 @@ + +Add Data to Hit Comparison Object — hc_add • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Add Data to Hit Comparison Object

    + + +
    + +
    +

    Adds a new entry to the hit comparison object for a specified condition.

    +
    + +
    + 
    hc_add(hc_obj, top_table, params_id, condition = 1, threshold = 0.05)
    +
    + +
    +

    Arguments

    + + +
    hc_obj
    +

    An object of class "hitcomp".

    + + +
    top_table
    +

    A dataframe containing the top table data.

    + + +
    params_id
    +

    A character string identifying the parameters +(max length 70).

    + + +
    condition
    +

    An integer (1 or 2) specifying the condition to which the +data belongs.

    + + +
    threshold
    +

    A numeric value specifying the adjusted p-value threshold.

    + +
    +
    +

    Value

    +

    The updated hit comparison object.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/hc_barplot.html b/docs/reference/hc_barplot.html new file mode 100644 index 0000000..8605461 --- /dev/null +++ b/docs/reference/hc_barplot.html @@ -0,0 +1,112 @@ + +Generate Barplot for Hit Comparison Object — hc_barplot • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Barplot for Hit Comparison Object

    + + +
    + +
    +

    Creates a barplot to visualize the number of significant features for each +parameter set in the hit comparison object.

    +
    + +
    + 
    hc_barplot(hc_obj)
    +
    + +
    +

    Arguments

    + + +
    hc_obj
    +

    An object of class "hitcomp" containing hit data for two +conditions.

    + +
    +
    +

    Value

    +

    A ggplot2 object representing the barplot.

    +
    +
    +

    See also

    +

    store_hits, ggplot2

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/hc_new.html b/docs/reference/hc_new.html new file mode 100644 index 0000000..2fcf330 --- /dev/null +++ b/docs/reference/hc_new.html @@ -0,0 +1,112 @@ + +Create New Hit Comparison Object — hc_new • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Create New Hit Comparison Object

    + + +
    + +
    +

    Creates a new hit comparison object with specified condition names.

    +
    + +
    + 
    hc_new(cond1name = "Condition 1", cond2name = "Condition 2")
    +
    + +
    +

    Arguments

    + + +
    cond1name
    +

    A character string for the first condition name +(max length 25).

    + + +
    cond2name
    +

    A character string for the second condition name +(max length 25).

    + +
    +
    +

    Value

    +

    An object of class "hitcomp" containing empty data lists +and condition names.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/hc_vennheatmap.html b/docs/reference/hc_vennheatmap.html new file mode 100644 index 0000000..2585c74 --- /dev/null +++ b/docs/reference/hc_vennheatmap.html @@ -0,0 +1,112 @@ + +Generate Venn Heatmap — hc_vennheatmap • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Venn Heatmap

    + + +
    + +
    +

    Creates a Venn heatmap to visualize the overlap of hits between two +conditions stored in a hit comparison object.

    +
    + +
    + 
    hc_vennheatmap(hc_obj)
    +
    + +
    +

    Arguments

    + + +
    hc_obj
    +

    An object of class "hitcomp" containing hit data for two +conditions.

    + +
    +
    +

    Value

    +

    A list containing the Venn heatmap plot and the number of hits.

    +
    +
    +

    See also

    +

    store_hits, pheatmap

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/hierarchical_clustering.html b/docs/reference/hierarchical_clustering.html new file mode 100644 index 0000000..1f41ed8 --- /dev/null +++ b/docs/reference/hierarchical_clustering.html @@ -0,0 +1,127 @@ + +Hierarchical Clustering of Curve Values — hierarchical_clustering • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Hierarchical Clustering of Curve Values

    + + +
    + +
    +

    Performs hierarchical clustering on given curve values. +It can automatically +determine the optimal number of clusters using silhouette analysis or use a +specified number. The function adjusts the provided top_table with cluster +assignments.

    +
    + +
    + 
    hierarchical_clustering(curve_values, k, smooth_timepoints, top_table)
    +
    + +
    +

    Arguments

    + + +
    curve_values
    +

    A matrix or data frame of curve values to cluster.

    + + +
    k
    +

    The number of clusters to use or "auto" to automatically determine +the optimal number using silhouette width analysis.

    + + +
    smooth_timepoints
    +

    Numeric vector of time points corresponding to +columns in curve_values.

    + + +
    top_table
    +

    Data frame to be updated with cluster assignments.

    + +
    +
    +

    Value

    +

    A list containing clustering results and the modified top_table.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/huge_table_user_prompter.html b/docs/reference/huge_table_user_prompter.html new file mode 100644 index 0000000..745975a --- /dev/null +++ b/docs/reference/huge_table_user_prompter.html @@ -0,0 +1,110 @@ + +Check if any table in a list has more than 300 rows and prompt user for input. — huge_table_user_prompter • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check if any table in a list has more than 300 rows and prompt user for input.

    + + +
    + +
    +

    This function iterates over a list of tables and checks if any table has + more than 300 rows. +If such a table is found, it prompts the user to proceed or stop.

    +
    + +
    + 
    huge_table_user_prompter(tables)
    +
    + +
    +

    Arguments

    + + +
    tables
    +

    A list of data frames.

    + +
    +
    +

    Value

    +

    NULL. This function is used for its side effects (prompting the +user and potentially stopping the script).

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/index.html b/docs/reference/index.html new file mode 100644 index 0000000..6eba92d --- /dev/null +++ b/docs/reference/index.html @@ -0,0 +1,587 @@ + +Package index • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Reference

    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +

    All functions

    +

    +
    +

    InputControl

    +

    InputControl: A class for controlling and validating inputs

    +

    Level3Functions

    +

    Level3Functions: A class for level 3 utility functions

    +

    Level4Functions

    +

    Level4Functions: A class for level 3 utility functions

    +

    NumericBlockFinder

    +

    NumericBlockFinder: A class for finding numeric blocks in data

    +

    SplineOmics SplineOmics-package

    +

    Package Name: SplineOmics

    +

    add_feature_names()

    +

    Add Feature Names to Data

    +

    add_plot_to_html()

    +

    Add Plot to HTML Content

    +

    ask_user()

    +

    Prompt the user with a yes/no question

    +

    between_level()

    +

    Between Level Analysis

    +

    bind_data_with_annotation()

    +

    Bind Data with Annotation

    +

    build_cluster_hits_report()

    +

    Build Cluster Hits Report

    +

    build_create_gsea_report()

    +

    Build GSEA Report

    +

    build_create_limma_report()

    +

    Build Cluster Hits Report

    +

    build_explore_data_report()

    +

    Build Explore Data Report

    +

    build_hyperparams_screen_report()

    +

    Build Hyperparameters Screening Report

    +

    check_between_level_pattern()

    +

    Check for Between-Level Patterns in Top Tables

    +

    check_clustered_hits()

    +

    Check Clustered Genes Dataframe for Required Conditions

    +

    check_databases()

    +

    Check Valid Databases Dataframe

    +

    check_genes()

    +

    Check Valid Gene IDs

    +

    check_null_elements()

    +

    Check for NULL Elements in Arguments

    +

    check_params()

    +

    Check Params List for Required Conditions

    +

    check_splineomics_elements()

    +

    Check for Required Elements in the SplineOmics Object

    +

    clean_gene_symbols()

    +

    Clean the Gene Symbols

    +

    cluster_hits()

    +

    cluster_hits.R contains the exported package function cluster_hits and all the functions that make up the functionality of cluster_hits. cluster_hits clusters the hits of a time series omics datasets (the features that were significantly changed over the time course) with hierarchical clustering of the spline shape. Cluster Hits from Top Tables

    +

    control_inputs_create_gsea_report()

    +

    Control Inputs for GSEA Report

    +

    control_inputs_extract_data()

    +

    Control Inputs for Extracting Data

    +

    create_enrichr_zip()

    +

    Create a ZIP File for Enrichr Gene Lists

    +

    create_gsea_report_level()

    +

    Perform Gene Set Enrichment Analysis and plot it.

    +

    create_limma_report()

    +

    Create a limma report

    +

    create_p_value_histogram()

    +

    Create a p-value histogram from a limma top_table

    +

    create_progress_bar()

    +

    utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. Create Progress Bar

    +

    create_spline_params()

    +

    Create Spline Parameters

    +

    create_splineomics()

    +

    Create and update the SplineOmics object =====

    +

    create_toc()

    +

    Create Table of Contents

    +

    create_volcano_plot()

    +

    Create a Volcano Plot

    +

    dbs_to_term2genes()

    +

    Convert Database File to TERM2GENE List

    +

    define_html_styles()

    +

    Define HTML Styles

    +

    design2design_matrix()

    +

    Create Design Matrix for Splines

    +

    download_enrichr_databases()

    +

    The exported function download_enrichr_databases allows to selects & download Enrichr databases for local use with clusterProfiler. Download Enrichr Databases

    +

    encode_df_to_base64()

    +

    Encode DataFrame to Base64 for HTML Embedding

    +

    enrichr_get_genesets()

    +

    Get Enrichr Gene Sets

    +

    ensure_clusterProfiler()

    +

    Ensure 'clusterProfiler' is installed and loaded

    +

    explore_data()

    +

    Generate Exploratory Plots

    +

    extract_data()

    +

    extract_data.R contains the exported package function extract_data. This function automatically recognises the data field in a table and returns the data matrix, that serves as input for the other functions of this package. This is for convenience only. Extract Numeric Matrix from Dataframe

    +

    flatten_spline_configs()

    +

    Flatten Spline Configurations

    +

    format_text()

    +

    Format text

    +

    gen_composite_spline_plots()

    +

    Generate Composite Spline Plots

    +

    gen_hitcomp_plots()

    +

    Generate Hit Comparison Plots

    +

    generate_and_write_html()

    +

    Generate and Write HTML Report

    +

    generate_avrg_diff_plots()

    +

    Generate Plots for Average Difference Conditions

    +

    generate_explore_plots()

    +

    Generate exploratory plots

    +

    generate_interaction_plots()

    +

    Generate Plots for Interaction of Condition and Time

    +

    generate_report_html()

    +

    utils scripts contains shared functions that are used by at least two package functions of the SplineOmics package. The level separation is only valid internally in this script, and has no connection to the script level of the respective exported functions scripts. Generate Report HTML

    +

    generate_reports()

    +

    Generate Reports

    +

    generate_reports_meta()

    +

    Generate Reports Metadata

    +

    generate_section_content()

    +

    Generate Section Content

    +

    generate_time_effect_plots()

    +

    Generate Plots for Time Effect

    +

    get_curve_values()

    +

    Calculate Curve Values Based on Top Table Filter

    +

    get_explore_plots_explanations()

    +

    Get Plot Explanations

    +

    get_header_section()

    +

    Get Header Section

    +

    get_level_hit_indices()

    +

    Get Hit Indices for a Specific Level

    +

    get_limma_combos_results()

    +

    Generate LIMMA Combination Results

    +

    get_spline_params_info()

    +

    Get Spline Parameters Info

    +

    hc_add()

    +

    Add Data to Hit Comparison Object

    +

    hc_barplot()

    +

    Generate Barplot for Hit Comparison Object

    +

    hc_new()

    +

    Create New Hit Comparison Object

    +

    hc_vennheatmap()

    +

    Generate Venn Heatmap

    +

    hierarchical_clustering()

    +

    Hierarchical Clustering of Curve Values

    +

    huge_table_user_prompter()

    +

    Check if any table in a list has more than 300 rows and prompt user for input.

    +

    is_not_na()

    +

    Check if Not All Values are NA

    +

    make_clustering_report()

    +

    Make Clustering Report

    +

    make_correlation_heatmaps()

    +

    Generate Correlation Heatmaps

    +

    make_density_plots()

    +

    Generate Density Plot

    +

    make_enrich_dotplot()

    +

    Make Enrich Dotplot

    +

    make_mds_plot()

    +

    Generate MDS Plot

    +

    make_pca_plot()

    +

    Generate PCA Plot with Dynamic Coloring

    +

    make_violin_box_plots()

    +

    Generate Violin Box Plot

    +

    manage_gsea_level()

    +

    Manage GSEA Analysis for a Specific Level

    +

    merge_annotation_all_levels_clustering()

    +

    Merge Annotation with All Top Tables

    +

    merge_top_table_with_annotation()

    +

    Merge Annotation with a Single Top Table

    +

    modify_limma_top_table()

    +

    Modify limma Top Table

    +

    normalize_curves()

    +

    Normalize Curve Values

    +

    open_template()

    +

    Open Template for Quick Setup

    +

    open_tutorial()

    +

    Interactive Tutorial for Getting Started

    +

    perform_clustering()

    +

    Perform Clustering

    +

    plot2base64()

    +

    Convert Plot to Base64

    +

    plot_all_mean_splines()

    +

    Plot All Mean Splines

    +

    plot_cluster_mean_splines()

    +

    Plot Consensus Shapes

    +

    plot_composite_splines()

    +

    Plot Composite Splines

    +

    plot_cv()

    +

    Coefficient of Variation (CV) Plot

    +

    plot_dendrogram()

    +

    Plot Dendrogram

    +

    plot_first_lag_autocorrelation()

    +

    First Lag Autocorrelation Coefficients Plot

    +

    plot_heatmap()

    +

    Plot Heatmap

    +

    plot_lag1_differences()

    +

    Lag-1 Differences Plot

    +

    plot_limma_combos_results()

    +

    Plot limma Combination Results

    +

    plot_mean_correlation_with_time()

    +

    Mean Correlation with Time Plot

    +

    plot_single_and_mean_splines()

    +

    Plot Single and Mean Splines

    +

    plot_splines()

    +

    Plot Splines for Features Based on Top Table Information

    +

    prepare_gene_lists_for_enrichr()

    +

    Prepare Gene Lists for Enrichr and Return as String

    +

    prepare_plot_data()

    +

    Prepare Plot Data

    +

    preprocess_rna_seq_data()

    +

    Perform default preprocessing of raw RNA-seq counts

    +

    print_info_message()

    +

    Print Informational Message

    +

    process_combo()

    +

    Process Combination

    +

    process_combo_pair()

    +

    Process Combination Pair

    +

    process_config_column()

    +

    Process Configuration Column

    +

    process_enrichment_results()

    +

    Process Enrichment Results

    +

    process_field()

    +

    Process and Encode Data Field for Report

    +

    process_level_cluster()

    +

    Process Level Cluster

    +

    process_plots()

    +

    Process Plots

    +

    process_result()

    +

    Process GSEA Result for a Specific Level

    +

    process_top_table()

    +

    Process Top Table

    +

    process_within_level()

    +

    Process Within Level

    +

    read_section_texts()

    +

    Read and split section texts from a file

    +

    remove_batch_effect()

    +

    Remove Batch Effect

    +

    remove_batch_effect_cluster_hits()

    +

    Remove Batch Effect from Cluster Hits

    +

    remove_prefix()

    +

    Remove Prefix from String

    +

    run_gsea()

    +

    Generate a GSEA Report

    +

    run_limma_splines()

    +

    run_limma_splines.R contains the exported package function run_limma_splines and all the functions that make up the functionality of run_limma_splines. run_limma_splines performs a limma analysis, using splines, to assign a p-value to every feature of a time series omics dataset, to find out which features are significantly changed over the time course. Run Limma Analysis with Spline Interpolation for Hyperparameter Screening

    +

    screen_limma_hyperparams()

    +

    screen_limma_hyperparams.R contains the exported package function screen_limma_hyperparams and all the functions that make up the functionality of screen_limma_hyperparams. screen_limma_hyperparams runs the other package function, run_limma_splines, for a time series omics dataset, for different hyperparameters. Such are for example degree of freedom of the spline, type of spline, limma design formula, and different versions of the data (full data vs. outliers removed). This can result in several combinations, and it is tedious analyzing the combination in an organised and structured manner. Therefore, this function streamlines that process. Limma Hyperparameters Screening

    +

    set_default_params()

    +

    Set Default Parameters

    +

    shorten_names()

    +

    Shorten Names

    +

    store_hits()

    +

    Store Hits

    +

    truncate_row_names()

    +

    Truncate Row Names

    +

    update_splineomics()

    +

    Update a SplineOmics object

    +

    within_level()

    +

    Within level analysis

    + + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/is_not_na.html b/docs/reference/is_not_na.html new file mode 100644 index 0000000..d474eea --- /dev/null +++ b/docs/reference/is_not_na.html @@ -0,0 +1,106 @@ + +Check if Not All Values are NA — is_not_na • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Check if Not All Values are NA

    + + +
    + +
    +

    Determines if a given atomic vector contains at least one non-NA value.

    +
    + +
    + 
    is_not_na(x)
    +
    + +
    +

    Arguments

    + + +
    x
    +

    An atomic vector or any other object.

    + +
    +
    +

    Value

    +

    TRUE if the vector contains at least one non-NA value or if the +object is not atomic; FALSE otherwise.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_clustering_report.html b/docs/reference/make_clustering_report.html new file mode 100644 index 0000000..fa9c7e7 --- /dev/null +++ b/docs/reference/make_clustering_report.html @@ -0,0 +1,218 @@ + +Make Clustering Report — make_clustering_report • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Make Clustering Report

    + + +
    + +
    +

    Generates a detailed clustering report including heatmaps, dendrograms, +curve plots, and consensus shapes for each level within a condition.

    +
    + +
    + 
    make_clustering_report(
+  all_levels_clustering,
+  condition,
+  data,
+  meta,
+  annotation,
+  genes,
+  spline_params,
+  adj_pthresholds,
+  report_dir,
+  mode,
+  report_info,
+  design,
+  meta_batch_column,
+  meta_batch2_column,
+  plot_info,
+  analysis_type,
+  feature_name_columns
+)
    +
    + +
    +

    Arguments

    + + +
    all_levels_clustering
    +

    A list containing clustering results for each +level within a condition.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    data
    +

    A matrix of data values.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    annotation
    +

    Dataframe containig the annotation info of the features, +such as gene and uniprotID, for example.

    + + +
    genes
    +

    Character vector containing the genes of the features.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    adj_pthresholds
    +

    Numeric vector, containing a float < 1 > 0 as each +value. There is one float for every level, and this is +the adj. p-value threshold.

    + + +
    report_dir
    +

    A character string specifying the report directory.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + + +
    report_info
    +

    An object containing report information.

    + + +
    design
    +

    A string representing the limma design formula

    + + +
    meta_batch_column
    +

    A character string specifying the meta batch column.

    + + +
    meta_batch2_column
    +

    A character string specifying the second meta +batch column.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + + +
    analysis_type
    +

    One of the strings "time_effect", "avrg_diff_conditions" +, or "interaction_condition_time". Those represent the +three different outputs of a limma analysis. For more +info on those 3 "categories", see package dir inst/ +descriptions/limma_result_categories.pdf.

    + + +
    feature_name_columns
    +

    Character vector containing the column names of +the annotation info that describe the features. +This argument is used to specify in the HTML +report how exactly the feature names displayed +above each individual spline plot have been +created. Use the same vector that was used to +create the row headers for the data matrix!

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_correlation_heatmaps.html b/docs/reference/make_correlation_heatmaps.html new file mode 100644 index 0000000..3c25754 --- /dev/null +++ b/docs/reference/make_correlation_heatmaps.html @@ -0,0 +1,122 @@ + +Generate Correlation Heatmaps — make_correlation_heatmaps • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Correlation Heatmaps

    + + +
    + +
    +

    This function generates correlation heatmaps using Spearman correlation for +a given data matrix. It creates a combined heatmap for all levels and +individual heatmaps for each level specified in the condition column of the +metadata.

    +
    + +
    + 
    make_correlation_heatmaps(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A numeric matrix containing the data.

    + + +
    meta
    +

    A dataframe containing the metadata.

    + + +
    condition
    +

    The column name in the metadata dataframe that contains the +factor levels for generating individual heatmaps.

    + +
    +
    +

    Value

    +

    A list of `ComplexHeatmap` heatmap objects representing the +correlation +heatmaps.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_density_plots.html b/docs/reference/make_density_plots.html new file mode 100644 index 0000000..6eeeae8 --- /dev/null +++ b/docs/reference/make_density_plots.html @@ -0,0 +1,115 @@ + +Generate Density Plot — make_density_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Density Plot

    + + +
    + +
    +

    This function generates a density plot for a given data matrix. The density +plot shows the distribution of the values in the data matrix.

    +
    + +
    + 
    make_density_plots(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A numeric matrix containing the data.

    + + +
    meta
    +

    A dataframe containing the column meta data of data

    + + +
    condition
    +

    The name of the factor column of meta for the experiment

    + +
    +
    +

    Value

    +

    A ggplot object representing the density plot.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_enrich_dotplot.html b/docs/reference/make_enrich_dotplot.html new file mode 100644 index 0000000..6f10718 --- /dev/null +++ b/docs/reference/make_enrich_dotplot.html @@ -0,0 +1,125 @@ + +Make Enrich Dotplot — make_enrich_dotplot • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Make Enrich Dotplot

    + + +
    + +
    +

    Make an enriched dotplot for visualization.

    +
    + +
    + 
    make_enrich_dotplot(enrichments_list, databases, title = "Title")
    +
    + +
    +

    Arguments

    + + +
    enrichments_list
    +

    A list of enrichments containing data frames for +different databases.

    + + +
    databases
    +

    A character vector specifying the databases to be included.

    + + +
    title
    +

    A character string specifying the title of the dotplot.

    + +
    +
    +

    Value

    +

    A list containing:

    p
    +

    The ggplot object representing the dotplot.

    + +
    dotplot_nrows
    +

    An integer specifying the number of rows in the + dotplot.

    + +
    full_enrich_results
    +

    A data frame containing the full enrichments + results.

    + + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_mds_plot.html b/docs/reference/make_mds_plot.html new file mode 100644 index 0000000..77bf01f --- /dev/null +++ b/docs/reference/make_mds_plot.html @@ -0,0 +1,118 @@ + +Generate MDS Plot — make_mds_plot • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate MDS Plot

    + + +
    + +
    +

    This function generates a multidimensional scaling (MDS) plot for a given +data matrix. The MDS plot visualizes the similarities or dissimilarities +between samples in the data matrix.

    +
    + +
    + 
    make_mds_plot(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A numeric matrix containing the data.

    + + +
    meta
    +

    A dataframe, containign the meta information of data.

    + + +
    condition
    +

    The column of the meta dataframe containign the levels that +separate the experiment.

    + +
    +
    +

    Value

    +

    A ggplot object representing the MDS plot.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_pca_plot.html b/docs/reference/make_pca_plot.html new file mode 100644 index 0000000..97cfb4b --- /dev/null +++ b/docs/reference/make_pca_plot.html @@ -0,0 +1,116 @@ + +Generate PCA Plot with Dynamic Coloring — make_pca_plot • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate PCA Plot with Dynamic Coloring

    + + +
    + +
    +

    This function generates a PCA plot from a data matrix, dynamically coloring +the points based on the levels of a specified factor in the metadata.

    +
    + +
    + 
    make_pca_plot(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A numeric matrix containing the data.

    + + +
    meta
    +

    A dataframe containing the metadata.

    + + +
    condition
    +

    The column name in the metadata dataframe that contains the +factor levels for coloring the PCA plot.

    + +
    +
    +

    Value

    +

    A ggplot object representing the PCA plot.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/make_violin_box_plots.html b/docs/reference/make_violin_box_plots.html new file mode 100644 index 0000000..efb2434 --- /dev/null +++ b/docs/reference/make_violin_box_plots.html @@ -0,0 +1,117 @@ + +Generate Violin Box Plot — make_violin_box_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate Violin Box Plot

    + + +
    + +
    +

    This function generates a violin plot for a given data matrix. The violin +plot shows the distribution of the values in the data matrix across different +variables, with each variable's distribution displayed as a separate violin.

    +
    + +
    + 
    make_violin_box_plots(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A numeric matrix containing the data.

    + + +
    meta
    +

    A dataframe containing the column meta data of data

    + + +
    condition
    +

    The name of the factor column of meta for the experiment

    + +
    +
    +

    Value

    +

    A ggplot object representing the violin plot.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/manage_gsea_level.html b/docs/reference/manage_gsea_level.html new file mode 100644 index 0000000..0f8d566 --- /dev/null +++ b/docs/reference/manage_gsea_level.html @@ -0,0 +1,131 @@ + +Manage GSEA Analysis for a Specific Level — manage_gsea_level • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Manage GSEA Analysis for a Specific Level

    + + +
    + +
    +

    This function manages the GSEA analysis for a specific level. It extracts +genes associated with the clustered hits, removes rows with `NA` values, +and runs the GSEA analysis using the `create_gsea_report` function.

    +
    + +
    + 
    manage_gsea_level(
+  clustered_hits,
+  level_name,
+  databases,
+  clusterProfiler_params
+)
    +
    + +
    +

    Arguments

    + + +
    clustered_hits
    +

    A dataframe containing the clustered hits for a +specific level. It must include a column named `feature` to extract genes.

    + + +
    level_name
    +

    A character string representing the name of the level.

    + + +
    databases
    +

    A list of databases for the gene set enrichment analysis.

    + + +
    clusterProfiler_params
    +

    Additional parameters for the GSEA analysis, +default is NA. Those include adj_p_value, +pAdjustMethod, etc (see clusterProfiler +documentation).

    + +
    +
    +

    Value

    +

    The result of the `create_gsea_report` function, which typically + includes various plots and enrichment results.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/merge_annotation_all_levels_clustering.html b/docs/reference/merge_annotation_all_levels_clustering.html new file mode 100644 index 0000000..0dd69b1 --- /dev/null +++ b/docs/reference/merge_annotation_all_levels_clustering.html @@ -0,0 +1,113 @@ + +Merge Annotation with All Top Tables — merge_annotation_all_levels_clustering • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Merge Annotation with All Top Tables

    + + +
    + +
    +

    This function merges annotation information into the `top_table` of each +non-logical element in a list.

    +
    + +
    + 
    merge_annotation_all_levels_clustering(all_levels_clustering, annotation)
    +
    + +
    +

    Arguments

    + + +
    all_levels_clustering
    +

    A list where each element contains a `top_table` +dataframe with a `feature_nr` column. Some elements may be logical values.

    + + +
    annotation
    +

    A dataframe containing the annotation information.

    + +
    +
    +

    Value

    +

    A list with updated `top_table` dataframes containing merged +annotation information.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/merge_top_table_with_annotation.html b/docs/reference/merge_top_table_with_annotation.html new file mode 100644 index 0000000..b58d06a --- /dev/null +++ b/docs/reference/merge_top_table_with_annotation.html @@ -0,0 +1,111 @@ + +Merge Annotation with a Single Top Table — merge_top_table_with_annotation • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Merge Annotation with a Single Top Table

    + + +
    + +
    +

    This function merges annotation information into a single `top_table` +dataframe based on the `feature_nr` column.

    +
    + +
    + 
    merge_top_table_with_annotation(top_table, annotation)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A dataframe containing the `top_table` with a `feature_nr` column.

    + + +
    annotation
    +

    A dataframe containing the annotation information.

    + +
    +
    +

    Value

    +

    A dataframe with updated `top_table` containing merged annotation information.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/modify_limma_top_table.html b/docs/reference/modify_limma_top_table.html new file mode 100644 index 0000000..232bca3 --- /dev/null +++ b/docs/reference/modify_limma_top_table.html @@ -0,0 +1,109 @@ + +Modify limma Top Table — modify_limma_top_table • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Modify limma Top Table

    + + +
    + +
    +

    Modifies the limma top table to include feature indices and names.

    +
    + +
    + 
    modify_limma_top_table(top_table, feature_names)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A dataframe containing the top table results from limma

    + + +
    feature_names
    +

    A character vector of feature names.

    + +
    +
    +

    Value

    +

    A tibble with feature indices and names included.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/normalize_curves.html b/docs/reference/normalize_curves.html new file mode 100644 index 0000000..103ca6e --- /dev/null +++ b/docs/reference/normalize_curves.html @@ -0,0 +1,119 @@ + +Normalize Curve Values — normalize_curves • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Normalize Curve Values

    + + +
    + +
    +

    This function normalizes each row in a data frame or matrix +of curve values. +Normalization is performed so that each row's values range from 0 +(corresponding to the +minimum value of the row) to 1 +(corresponding to the maximum value of the row).

    +
    + +
    + 
    normalize_curves(curve_values)
    +
    + +
    +

    Arguments

    + + +
    curve_values
    +

    A data frame or matrix of curve values where each row +represents + a curve and each column a time point.

    + +
    +
    +

    Value

    +

    A data frame or matrix with the same dimensions as the input, where + each row + has been normalized.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/open_template.html b/docs/reference/open_template.html new file mode 100644 index 0000000..89b277f --- /dev/null +++ b/docs/reference/open_template.html @@ -0,0 +1,97 @@ + +Open Template for Quick Setup — open_template • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Open Template for Quick Setup

    + + +
    + +
    +

    This function opens the `template.Rmd` file in RStudio for +interactive use. The template file provides a structure for users +to quickly set up their personal analysis.

    +
    + +
    + 
    open_template()
    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/open_tutorial.html b/docs/reference/open_tutorial.html new file mode 100644 index 0000000..fd8221c --- /dev/null +++ b/docs/reference/open_tutorial.html @@ -0,0 +1,95 @@ + +Interactive Tutorial for Getting Started — open_tutorial • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Interactive Tutorial for Getting Started

    + + +
    + +
    +

    This function opens the `tutorial.Rmd` file in RStudio for +interactive use. Users can then run each code chunk step by step.

    +
    + +
    + 
    open_tutorial()
    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/perform_clustering.html b/docs/reference/perform_clustering.html new file mode 100644 index 0000000..392bc5b --- /dev/null +++ b/docs/reference/perform_clustering.html @@ -0,0 +1,133 @@ + +Perform Clustering — perform_clustering • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Perform Clustering

    + + +
    + +
    +

    Performs clustering on top tables using specified p-values and clusters +for each level within a condition.

    +
    + +
    + 
    perform_clustering(top_tables, clusters, meta, condition, spline_params, mode)
    +
    + +
    +

    Arguments

    + + +
    top_tables
    +

    A list of top tables from limma analysis.

    + + +
    clusters
    +

    A list specifying clusters or "auto" for automatic +estimation.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + +
    +
    +

    Value

    +

    A list of clustering results for each level within the condition.

    +
    +
    +

    See also

    +

    process_level_cluster

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot2base64.html b/docs/reference/plot2base64.html new file mode 100644 index 0000000..29d3a7d --- /dev/null +++ b/docs/reference/plot2base64.html @@ -0,0 +1,143 @@ + +Convert Plot to Base64 — plot2base64 • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Convert Plot to Base64

    + + +
    + +
    +

    Converts a ggplot2 plot to a Base64-encoded PNG image and returns an HTML +img tag for embedding in a report.

    +
    + +
    + 
    plot2base64(
+  plot,
+  height,
+  width = 7,
+  base_height_per_row = 2.5,
+  units = "in",
+  html_img_width = "100%"
+)
    +
    + +
    +

    Arguments

    + + +
    plot
    +

    A ggplot2 plot object.

    + + +
    height
    +

    An integer specifying the height of the plot for correct +representation in the HTML.

    + + +
    width
    +

    A numeric value specifying the width of the plot in inches.

    + + +
    base_height_per_row
    +

    A numeric value specifying the base height per +row in inches.

    + + +
    units
    +

    A character string specifying the units for the width and +height.

    + + +
    html_img_width
    +

    A character string specifying the width of the image +in HTML.

    + +
    +
    +

    Value

    +

    A character string containing an HTML img tag with the Base64-encoded + plot.

    +
    +
    +

    See also

    +

    dataURI

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_all_mean_splines.html b/docs/reference/plot_all_mean_splines.html new file mode 100644 index 0000000..7eca770 --- /dev/null +++ b/docs/reference/plot_all_mean_splines.html @@ -0,0 +1,119 @@ + +Plot All Mean Splines — plot_all_mean_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot All Mean Splines

    + + +
    + +
    +

    Generates a plot of average curves for each cluster, showing min-max +normalized intensities over time.

    +
    + +
    + 
    plot_all_mean_splines(curve_values, plot_info)
    +
    + +
    +

    Arguments

    + + +
    curve_values
    +

    A dataframe containing curve values and cluster +assignments.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + +
    +
    +

    Value

    +

    A ggplot object representing the average curves by cluster.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_cluster_mean_splines.html b/docs/reference/plot_cluster_mean_splines.html new file mode 100644 index 0000000..a129f46 --- /dev/null +++ b/docs/reference/plot_cluster_mean_splines.html @@ -0,0 +1,123 @@ + +Plot Consensus Shapes — plot_cluster_mean_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Consensus Shapes

    + + +
    + +
    +

    Generates composite plots of single and consensus shapes for each cluster +of curve values.

    +
    + +
    + 
    plot_cluster_mean_splines(curve_values, plot_info)
    +
    + +
    +

    Arguments

    + + +
    curve_values
    +

    A dataframe containing curve values and cluster +assignments.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + +
    +
    +

    Value

    +

    A list containing a plot for every cluster

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_composite_splines.html b/docs/reference/plot_composite_splines.html new file mode 100644 index 0000000..5c89a5c --- /dev/null +++ b/docs/reference/plot_composite_splines.html @@ -0,0 +1,153 @@ + +Plot Composite Splines — plot_composite_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Composite Splines

    + + +
    + +
    +

    Generates composite spline plots for significant and non-significant +features based on the specified indices.

    +
    + +
    + 
    plot_composite_splines(
+  data,
+  meta,
+  spline_test_configs,
+  top_table,
+  top_table_name,
+  indices,
+  type,
+  time_unit_label
+)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A matrix of data values.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    top_table
    +

    A dataframe containing the top table results.

    + + +
    top_table_name
    +

    A character string specifying the name of the +top table.

    + + +
    indices
    +

    A vector of indices specifying which features to plot.

    + + +
    type
    +

    A character string specifying the type of features ('significant' +or 'not_significant').

    + + +
    time_unit_label
    +

    A string shown in the plots as the unit for the time, +such as min or hours.

    + +
    +
    +

    Value

    +

    A list containing the composite plot and its length if plots are +generated, FALSE otherwise.

    +
    +
    +

    See also

    +

    bs, ns, ggplot2, +wrap_plots

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_cv.html b/docs/reference/plot_cv.html new file mode 100644 index 0000000..c8a9cae --- /dev/null +++ b/docs/reference/plot_cv.html @@ -0,0 +1,128 @@ + +Coefficient of Variation (CV) Plot — plot_cv • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Coefficient of Variation (CV) Plot

    + + +
    + +
    +

    This function takes a data frame with time series data +(rows as features and columns as samples), +a meta table with sample information including time points and conditions, +computes the coefficient +of variation (CV) for each feature for each condition level, and plots the +distribution of these +CVs.

    +
    + +
    + 
    plot_cv(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A data frame where rows are features and columns are samples.

    + + +
    meta
    +

    A data frame with sample metadata. Must contain a column "Time" +and the condition column.

    + + +
    condition
    +

    The name of the column in the meta table that contains the +condition information.

    + +
    +
    +

    Value

    +

    A list of ggplot2 objects, each showing the distribution of CVs for + one condition.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_dendrogram.html b/docs/reference/plot_dendrogram.html new file mode 100644 index 0000000..c38093c --- /dev/null +++ b/docs/reference/plot_dendrogram.html @@ -0,0 +1,116 @@ + +Plot Dendrogram — plot_dendrogram • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Dendrogram

    + + +
    + +
    +

    Generates a dendrogram plot for hierarchical clustering results, +colored by clusters.

    +
    + +
    + 
    plot_dendrogram(hc, k)
    +
    + +
    +

    Arguments

    + + +
    hc
    +

    A hierarchical clustering object.

    + + +
    k
    +

    An integer specifying the number of clusters.

    + +
    +
    +

    Value

    +

    A ggplot object representing the dendrogram.

    +
    +
    +

    See also

    +

    color_branches, as.ggdend, +ggplot2

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_first_lag_autocorrelation.html b/docs/reference/plot_first_lag_autocorrelation.html new file mode 100644 index 0000000..67508f7 --- /dev/null +++ b/docs/reference/plot_first_lag_autocorrelation.html @@ -0,0 +1,128 @@ + +First Lag Autocorrelation Coefficients Plot — plot_first_lag_autocorrelation • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    First Lag Autocorrelation Coefficients Plot

    + + +
    + +
    +

    This function takes a data frame with time series data +(rows as features and columns as samples), +a meta table with sample information including time points and conditions, +computes the first lag +autocorrelation for each feature for each condition level, and plots the +distribution of these +autocorrelation coefficients.

    +
    + +
    + 
    plot_first_lag_autocorrelation(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A data frame where rows are features and columns are samples.

    + + +
    meta
    +

    A data frame with sample metadata. Must contain a column "Time" +and the condition column.

    + + +
    condition
    +

    The name of the column in the meta table that contains the +condition information.

    + +
    +
    +

    Value

    +

    A list of ggplot2 objects, each showing the distribution of first +lag autocorrelation coefficients for one condition.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_heatmap.html b/docs/reference/plot_heatmap.html new file mode 100644 index 0000000..c242acf --- /dev/null +++ b/docs/reference/plot_heatmap.html @@ -0,0 +1,142 @@ + +Plot Heatmap — plot_heatmap • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Heatmap

    + + +
    + +
    +

    Generates heatmaps for each level within a condition, showing z-scores of +log2 intensity values, split by clusters.

    +
    + +
    + 
    plot_heatmap(
+  datas,
+  meta,
+  mode,
+  condition,
+  all_levels_clustering,
+  time_unit_label
+)
    +
    + +
    +

    Arguments

    + + +
    datas
    +

    A matrix of data values.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    mode
    +

    A character vector with length 1, specifying the type of limma +design formula (integrated for formulas with interaction effects +between the levels, isolated for formulas where each level is +analysed in isolation (no interaction effects))

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    all_levels_clustering
    +

    A list containing clustering results for each +level within the condition.

    + + +
    time_unit_label
    +

    A character string specifying the time unit label.

    + +
    +
    +

    Value

    +

    A list of ComplexHeatmap heatmap objects for each level.

    +
    +
    +

    See also

    +

    Heatmap, arrange

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_lag1_differences.html b/docs/reference/plot_lag1_differences.html new file mode 100644 index 0000000..9c56fab --- /dev/null +++ b/docs/reference/plot_lag1_differences.html @@ -0,0 +1,128 @@ + +Lag-1 Differences Plot — plot_lag1_differences • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Lag-1 Differences Plot

    + + +
    + +
    +

    This function takes a data frame with time series data +(rows as features and columns as samples), +a meta table with sample information including time points and conditions, +computes the lag-1 +differences for each feature for each condition level, and plots the +distribution of these +differences.

    +
    + +
    + 
    plot_lag1_differences(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A data frame where rows are features and columns are samples.

    + + +
    meta
    +

    A data frame with sample metadata. Must contain a column "Time" +and the condition column.

    + + +
    condition
    +

    The name of the column in the meta table that contains the +condition information.

    + +
    +
    +

    Value

    +

    A list of ggplot2 objects, each showing the distribution of lag-1 +differences for one condition.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_limma_combos_results.html b/docs/reference/plot_limma_combos_results.html new file mode 100644 index 0000000..e9caa58 --- /dev/null +++ b/docs/reference/plot_limma_combos_results.html @@ -0,0 +1,149 @@ + +Plot limma Combination Results — plot_limma_combos_results • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot limma Combination Results

    + + +
    + +
    +

    Generates plots for pairwise comparisons of hyperparameter combinations +using limma results.

    +
    + +
    + 
    plot_limma_combos_results(
+  top_tables_combos,
+  datas,
+  metas,
+  condition,
+  spline_test_configs,
+  meta_batch_column,
+  meta_batch2_column,
+  time_unit = time_unit
+)
    +
    + +
    +

    Arguments

    + + +
    top_tables_combos
    +

    A list of top tables for each combination.

    + + +
    datas
    +

    A list of matrices.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +
    condition
    +

    Meta column name that contains the levels.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    meta_batch_column
    +

    A character string specifying the meta batch column.

    + + +
    meta_batch2_column
    +

    A character string specifying the second meta batch +column.

    + + +
    time_unit
    +

    A single character, such as s, m, h, or d, specifying the +time_unit that should be used for the plots (s = seconds, m = minutes, +h = hours, d = days). This single character will be converted to a string +that is a little bit more verbose, such as sec in square brackets for s.

    + +
    +
    +

    Value

    +

    A list of results including hit comparison plots and composite +spline plots for each pair of combinations.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_mean_correlation_with_time.html b/docs/reference/plot_mean_correlation_with_time.html new file mode 100644 index 0000000..43a4e51 --- /dev/null +++ b/docs/reference/plot_mean_correlation_with_time.html @@ -0,0 +1,124 @@ + +Mean Correlation with Time Plot — plot_mean_correlation_with_time • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Mean Correlation with Time Plot

    + + +
    + +
    +

    This function takes a data frame with time series data +(rows as features and columns as samples) +and a meta table with sample information including time points, computes +the correlation of each +feature with time, and plots the distribution of these correlations.

    +
    + +
    + 
    plot_mean_correlation_with_time(data, meta, condition)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A data frame where rows are features and columns are samples.

    + + +
    meta
    +

    A data frame with sample metadata. Must contain a column "Time".

    + + +
    condition
    +

    The column of the meta dataframe containign the levels that +separate the experiment.

    + +
    +
    +

    Value

    +

    A ggplot2 object showing the distribution of mean correlations + with time.

    +

    @importFrom rlang .data

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_single_and_mean_splines.html b/docs/reference/plot_single_and_mean_splines.html new file mode 100644 index 0000000..2c38871 --- /dev/null +++ b/docs/reference/plot_single_and_mean_splines.html @@ -0,0 +1,126 @@ + +Plot Single and Mean Splines — plot_single_and_mean_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Single and Mean Splines

    + + +
    + +
    +

    Generates a plot showing individual time series shapes and their consensus +(mean) shape.

    +
    + +
    + 
    plot_single_and_mean_splines(time_series_data, title, plot_info)
    +
    + +
    +

    Arguments

    + + +
    time_series_data
    +

    A dataframe or matrix with time series data.

    + + +
    title
    +

    A character string specifying the title of the plot.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + +
    +
    +

    Value

    +

    A ggplot object representing the single and consensus shapes.

    +
    +
    +

    See also

    +

    ggplot2

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/plot_splines.html b/docs/reference/plot_splines.html new file mode 100644 index 0000000..dec4a6c --- /dev/null +++ b/docs/reference/plot_splines.html @@ -0,0 +1,159 @@ + +Plot Splines for Features Based on Top Table Information — plot_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Plot Splines for Features Based on Top Table Information

    + + +
    + +
    +

    This function generates plots for each feature listed in the +top table using spline +interpolation for fitted values. It creates individual plots for each feature +and combines +them into a single composite plot. The function is internal and not exported.

    +
    + +
    + 
    plot_splines(
+  top_table,
+  data,
+  meta,
+  X,
+  time_unit_label,
+  plot_info,
+  adj_pthreshold
+)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A dataframe containing the indices and names of features, +along with their + statistical metrics such as intercepts and spline + coefficients.

    + + +
    data
    +

    A matrix or dataframe containing the raw data values for each +feature.

    + + +
    meta
    +

    A dataframe containing metadata for the data, including time +points.

    + + +
    X
    +

    The limma design matrix that defines the experimental conditions.

    + + +
    time_unit_label
    +

    A string shown in the plots as the unit for the time, +such as min or hours.

    + + +
    plot_info
    +

    List containing the elements y_axis_label (string), +time_unit (string), treatment_labels (character vector), +treatment_timepoints (integer vector). All can also be NA. +This list is used to add this info to the spline plots. +time_unit is used to label the x-axis, and treatment_labels +and -timepoints are used to create vertical dashed lines, +indicating the positions of the treatments (such as +feeding, temperature shift, etc.).

    + + +
    adj_pthreshold
    +

    Double > 0 and < 1 specifying the adj. p-val threshold.

    + +
    +
    +

    Value

    +

    A list containing the composite plot and the number of rows used in +the plot layout.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/prepare_gene_lists_for_enrichr.html b/docs/reference/prepare_gene_lists_for_enrichr.html new file mode 100644 index 0000000..66424f6 --- /dev/null +++ b/docs/reference/prepare_gene_lists_for_enrichr.html @@ -0,0 +1,114 @@ + +Prepare Gene Lists for Enrichr and Return as String — prepare_gene_lists_for_enrichr • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Prepare Gene Lists for Enrichr and Return as String

    + + +
    + +
    +

    This function processes the clustered hits in each element of +`all_levels_clustering`, formats the gene names for easy copy-pasting into +Enrichr, and returns the formatted gene lists as a string.

    +
    + +
    + 
    prepare_gene_lists_for_enrichr(all_levels_clustering, genes)
    +
    + +
    +

    Arguments

    + + +
    all_levels_clustering
    +

    A list where each element contains a dataframe +`clustered_hits` with columns `feature` and `cluster`.

    + + +
    genes
    +

    A vector of gene names corresponding to the feature indices.

    + +
    +
    +

    Value

    +

    A character vector with the formatted gene lists for each cluster.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/prepare_plot_data.html b/docs/reference/prepare_plot_data.html new file mode 100644 index 0000000..637ee59 --- /dev/null +++ b/docs/reference/prepare_plot_data.html @@ -0,0 +1,120 @@ + +Prepare Plot Data — prepare_plot_data • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Prepare Plot Data

    + + +
    + +
    +

    This function prepares plot data for visualization based on enrichments +lists and specified databases.

    +
    + +
    + 
    prepare_plot_data(enrichments_list, databases)
    +
    + +
    +

    Arguments

    + + +
    enrichments_list
    +

    A list of enrichments containing data frames for +different databases.

    + + +
    databases
    +

    A character vector specifying the databases to be included.

    + +
    +
    +

    Value

    +

    A list containing two data frames:

    top_plot_data
    +

    A data frame containing the prepared plot data for + visualization of top combinations.

    + +
    full_enrich_results
    +

    A data frame containing the full enrichments + results.

    + + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/preprocess_rna_seq_data.html b/docs/reference/preprocess_rna_seq_data.html new file mode 100644 index 0000000..f7891c6 --- /dev/null +++ b/docs/reference/preprocess_rna_seq_data.html @@ -0,0 +1,124 @@ + +Perform default preprocessing of raw RNA-seq counts — preprocess_rna_seq_data • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Perform default preprocessing of raw RNA-seq counts

    + + +
    + +
    +

    This function is called when `preprocess_rna_seq` is `TRUE`. It performs the +default preprocessing steps for raw RNA-seq counts, including creating a +`DGEList` object, normalizing the counts, and applying the `voom` +transformation.

    +
    + +
    + 
    preprocess_rna_seq_data(raw_counts, design_matrix, normalize_func = NULL)
    +
    + +
    +

    Arguments

    + + +
    raw_counts
    +

    A matrix of raw RNA-seq counts (genes as rows, samples as +columns).

    + + +
    design_matrix
    +

    A design matrix used in the linear modeling, typically +specifying the experimental conditions.

    + + +
    normalize_func
    +

    An optional normalization function. If provided, this +function will be used to normalize the `DGEList` object. If not provided, + TMM normalization (via `edgeR::calcNormFactors`) will be used by default.

    + +
    +
    +

    Value

    +

    A `voom` object, which includes the log2-counts per million (logCPM) + matrix and observation-specific weights.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/print_info_message.html b/docs/reference/print_info_message.html new file mode 100644 index 0000000..bfa9721 --- /dev/null +++ b/docs/reference/print_info_message.html @@ -0,0 +1,105 @@ + +Print Informational Message — print_info_message • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Print Informational Message

    + + +
    + +
    +

    This function prints a nicely formatted informational message with a green "Info" label.

    +
    + +
    + 
    print_info_message(message_prefix, report_dir)
    +
    + +
    +

    Arguments

    + + +
    message_prefix
    +

    A custom message prefix to be displayed before the success message.

    + + +
    report_dir
    +

    The directory where the HTML reports are located.

    + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_combo.html b/docs/reference/process_combo.html new file mode 100644 index 0000000..1644fd7 --- /dev/null +++ b/docs/reference/process_combo.html @@ -0,0 +1,176 @@ + +Process Combination — process_combo • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Combination

    + + +
    + +
    +

    Processes a single combination of data, design, spline configuration, and +p-threshold to generate LIMMA spline results.

    +
    + +
    + 
    process_combo(
+  data_index,
+  design_index,
+  spline_config_index,
+  pthreshold,
+  datas,
+  metas,
+  designs,
+  modes,
+  condition,
+  spline_test_configs,
+  feature_names,
+  padjust_method,
+  ...
+)
    +
    + +
    +

    Arguments

    + + +
    data_index
    +

    Index of the data in the datas list.

    + + +
    design_index
    +

    Index of the design in the designs list.

    + + +
    spline_config_index
    +

    Index of the spline configuration in the +spline_test_configs list.

    + + +
    pthreshold
    +

    The p-value threshold for significance.

    + + +
    datas
    +

    A list of data matrices

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +
    designs
    +

    A list of design matrices.

    + + +
    modes
    +

    A character vector containing 'isolated' or 'integrated'.

    + + +
    condition
    +

    A single character string specifying the condition.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    feature_names
    +

    A character vector of feature names.

    + + +
    padjust_method
    +

    A single character string specifying the p-adjustment +method.

    + + +
    ...
    +

    Additional arguments.

    + +
    +
    +

    Value

    +

    A list of top tables from the LIMMA spline analysis.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_combo_pair.html b/docs/reference/process_combo_pair.html new file mode 100644 index 0000000..43e1752 --- /dev/null +++ b/docs/reference/process_combo_pair.html @@ -0,0 +1,134 @@ + +Process Combination Pair — process_combo_pair • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Combination Pair

    + + +
    + +
    +

    Processes a combination pair to generate plots and compile them into an +HTML report.

    +
    + +
    + 
    process_combo_pair(
+  combo_pair,
+  combo_pair_name,
+  report_info,
+  report_dir,
+  timestamp
+)
    +
    + +
    +

    Arguments

    + + +
    combo_pair
    +

    A list containing hit comparison and composite spline +plots.

    + + +
    combo_pair_name
    +

    A character string for naming the combination pair.

    + + +
    report_info
    +

    An object containing report information.

    + + +
    report_dir
    +

    A non-empty string specifying the report directory.

    + + +
    timestamp
    +

    A timestamp to include in the report filename.

    + +
    +
    +

    Value

    +

    No return value, called for side effects.

    +
    +
    +

    See also

    +

    generate_report_html

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_config_column.html b/docs/reference/process_config_column.html new file mode 100644 index 0000000..eff8f17 --- /dev/null +++ b/docs/reference/process_config_column.html @@ -0,0 +1,121 @@ + +Process Configuration Column — process_config_column • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Configuration Column

    + + +
    + +
    +

    Processes a configuration column based on the given mode and number of +levels.

    +
    + +
    + 
    process_config_column(config_column, index, num_levels, mode)
    +
    + +
    +

    Arguments

    + + +
    config_column
    +

    A configuration column from the spline test +configurations.

    + + +
    index
    +

    Index of the configuration to process.

    + + +
    num_levels
    +

    Number of unique levels in the metadata condition.

    + + +
    mode
    +

    A character string specifying the mode +('integrated' or 'isolated').

    + +
    +
    +

    Value

    +

    A vector or list with the processed configuration values.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_enrichment_results.html b/docs/reference/process_enrichment_results.html new file mode 100644 index 0000000..429bea1 --- /dev/null +++ b/docs/reference/process_enrichment_results.html @@ -0,0 +1,134 @@ + +Process Enrichment Results — process_enrichment_results • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Enrichment Results

    + + +
    + +
    +

    Process enrichment results for visualization.

    +
    + +
    + 
    process_enrichment_results(
+  all_db_results,
+  enrichment_results,
+  adjP_threshold,
+  column_name,
+  count_column_name,
+  background = FALSE
+)
    +
    + +
    +

    Arguments

    + + +
    all_db_results
    +

    A list of data frames containing enrichment results +for all databases.

    + + +
    enrichment_results
    +

    A list of data frames containing enrichment +results for individual databases.

    + + +
    adjP_threshold
    +

    The threshold for adjusted p-values.

    + + +
    column_name
    +

    The name of the column to store adjusted p-values.

    + + +
    count_column_name
    +

    The name of the column to store gene counts.

    + + +
    background
    +

    Logical indicating whether background ratios are included.

    + +
    +
    +

    Value

    +

    A list of data frames containing processed enrichment results.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_field.html b/docs/reference/process_field.html new file mode 100644 index 0000000..26b3e68 --- /dev/null +++ b/docs/reference/process_field.html @@ -0,0 +1,149 @@ + +Process and Encode Data Field for Report — process_field • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process and Encode Data Field for Report

    + + +
    + +
    +

    This function processes a given field, encodes the associated data as base64, +and generates a download link for the report. It handles different types of +fields including data, meta, top tables, and Enrichr formatted gene lists.

    +
    + +
    + 
    process_field(
+  field,
+  data,
+  meta,
+  topTables,
+  report_info,
+  encode_df_to_base64,
+  report_type,
+  enrichr_format
+)
    +
    + +
    +

    Arguments

    + + +
    field
    +

    A string specifying the field to process.

    + + +
    data
    +

    A dataframe containing the main data.

    + + +
    meta
    +

    A dataframe containing meta information.

    + + +
    topTables
    +

    A dataframe containing the results of differential +expression analysis.

    + + +
    report_info
    +

    A list containing additional report information.

    + + +
    encode_df_to_base64
    +

    A function to encode a dataframe to base64.

    + + +
    report_type
    +

    A string specifying the type of report.

    + + +
    enrichr_format
    +

    A list with the formatted gene lists and background +gene list.

    + +
    +
    +

    Value

    +

    A string containing the HTML link for downloading the processed + field.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_level_cluster.html b/docs/reference/process_level_cluster.html new file mode 100644 index 0000000..a84f139 --- /dev/null +++ b/docs/reference/process_level_cluster.html @@ -0,0 +1,146 @@ + +Process Level Cluster — process_level_cluster • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Level Cluster

    + + +
    + +
    +

    Processes clustering for a specific level within a condition using the +provided top table and spline parameters.

    +
    + +
    + 
    process_level_cluster(
+  top_table,
+  cluster_size,
+  level,
+  meta,
+  condition,
+  spline_params,
+  mode
+)
    +
    + +
    +

    Arguments

    + + +
    top_table
    +

    A dataframe containing the top table results from limma.

    + + +
    cluster_size
    +

    The size of clusters to generate.

    + + +
    level
    +

    The level within the condition to process.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + +
    +
    +

    Value

    +

    A list containing the clustering results, including curve values and + the design matrix.

    +
    + + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_plots.html b/docs/reference/process_plots.html new file mode 100644 index 0000000..369209a --- /dev/null +++ b/docs/reference/process_plots.html @@ -0,0 +1,133 @@ + +Process Plots — process_plots • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Plots

    + + +
    + +
    +

    Converts plots to base64 and appends them to the HTML content.

    +
    + +
    + 
    process_plots(
+  plots_element,
+  plots_size,
+  html_content,
+  toc,
+  header_index,
+  element_name = NA
+)
    +
    + +
    +

    Arguments

    + + +
    plots_element
    +

    A list of plots to be processed.

    + + +
    plots_size
    +

    A list of sizes for the plots.

    + + +
    html_content
    +

    The current state of the HTML content.

    + + +
    toc
    +

    The current state of the table of contents (TOC).

    + + +
    header_index
    +

    An index to uniquely identify each section +for anchoring.

    + + +
    element_name
    +

    A character string specifying the name of the element.

    + +
    +
    +

    Value

    +

    Updated HTML content with the plots included.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_result.html b/docs/reference/process_result.html new file mode 100644 index 0000000..40c6fa2 --- /dev/null +++ b/docs/reference/process_result.html @@ -0,0 +1,125 @@ + +Process GSEA Result for a Specific Level — process_result • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process GSEA Result for a Specific Level

    + + +
    + +
    +

    This function processes the GSEA result for a specific level. It handles +cases where the result contains `NA` values by adding a section break. +Otherwise, it extracts the plot, plot size, and header information from +the result.

    +
    + +
    + 
    process_result(level_result, level_name)
    +
    + +
    +

    Arguments

    + + +
    level_result
    +

    A list containing the GSEA result for a specific level.

    + + +
    level_name
    +

    A character string representing the name of the level.

    + +
    +
    +

    Value

    +

    A list with the following components:

    plot
    +

    A plot object or "section_break" if the result contains `NA`.

    + +
    plot_size
    +

    An integer indicating the size of the plot.

    + +
    header_info
    +

    A list with header information, including the level + name, full enrichment results, and raw enrichment results if available.

    + + +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_top_table.html b/docs/reference/process_top_table.html new file mode 100644 index 0000000..64427e9 --- /dev/null +++ b/docs/reference/process_top_table.html @@ -0,0 +1,118 @@ + +Process Top Table — process_top_table • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Top Table

    + + +
    + +
    +

    Processes the top table from a LIMMA analysis, adding feature names and +intercepts.

    +
    + +
    + 
    process_top_table(process_within_level_result, feature_names)
    +
    + +
    +

    Arguments

    + + +
    process_within_level_result
    +

    List of lists containing the limma +topTable, fit, and optionally the voom +object. All of this is from one specific +level.

    + + +
    feature_names
    +

    A non-empty character vector of feature names.

    + +
    +
    +

    Value

    +

    A dataframe containing the processed top table with added intercepts.

    +
    +
    +

    See also

    +

    modify_limma_top_table, lmFit

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/process_within_level.html b/docs/reference/process_within_level.html new file mode 100644 index 0000000..126d161 --- /dev/null +++ b/docs/reference/process_within_level.html @@ -0,0 +1,152 @@ + +Process Within Level — process_within_level • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Process Within Level

    + + +
    + +
    +

    Performs a within-level analysis using limma to generate top tables and fit +objects based on the specified spline parameters. Performs the limma spline +analysis for a selected level of a factor

    +
    + +
    + 
    process_within_level(
+  data,
+  preprocess_rna_seq,
+  normalization_fun,
+  meta,
+  design,
+  spline_params,
+  level_index,
+  padjust_method
+)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A matrix of data values.

    + + +
    preprocess_rna_seq
    +

    Boolean specifying whether to preprocess RNA seq

    + + +
    normalization_fun
    +

    Function for normalizing RNA-seq raw counts.

    + + +
    meta
    +

    A dataframe containing metadata, including a 'Time' column.

    + + +
    design
    +

    A design formula or matrix for the limma analysis.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    level_index
    +

    The index of the level within the factor.

    + + +
    padjust_method
    +

    A character string specifying the p-adjustment method.

    + +
    +
    +

    Value

    +

    A list containing the top table and the fit object from the limma +analysis.

    +
    +
    +

    See also

    +

    bs, ns, lmFit, +eBayes, topTable

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/read_section_texts.html b/docs/reference/read_section_texts.html new file mode 100644 index 0000000..4f186ea --- /dev/null +++ b/docs/reference/read_section_texts.html @@ -0,0 +1,112 @@ + +Read and split section texts from a file — read_section_texts • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Read and split section texts from a file

    + + +
    + +
    +

    This internal function reads the contents of a text file located in the +`inst/descriptions` directory of the package and splits it into individual +sections based on a specified delimiter.

    +
    + +
    + 
    read_section_texts(filename)
    +
    + +
    +

    Arguments

    + + +
    filename
    +

    A character string specifying the name of the file +containing the section texts. The file should be located in the +`inst/descriptions` directory of the package.

    + +
    +
    +

    Value

    +

    A character vector where each element is a section of the text +split by the delimiter `|`.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/remove_batch_effect.html b/docs/reference/remove_batch_effect.html new file mode 100644 index 0000000..7ea0153 --- /dev/null +++ b/docs/reference/remove_batch_effect.html @@ -0,0 +1,136 @@ + +Remove Batch Effect — remove_batch_effect • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Remove Batch Effect

    + + +
    + +
    +

    Removes batch effects from the data matrices using the specified batch +column in the metadata.

    +
    + +
    + 
    remove_batch_effect(
+  datas,
+  metas,
+  meta_batch_column,
+  meta_batch2_column,
+  condition
+)
    +
    + +
    +

    Arguments

    + + +
    datas
    +

    A list of matrices.

    + + +
    metas
    +

    A list of metadata corresponding to the data matrices.

    + + +
    meta_batch_column
    +

    A character string specifying the meta batch column.

    + + +
    meta_batch2_column
    +

    A character string specifying the second meta batch +column.

    + + +
    condition
    +

    A character vector of length 1, specifying the column name +of the meta dataframe, that contains the levels that +separate the experiment.

    + +
    +
    +

    Value

    +

    A list of matrices with batch effects removed where applicable.

    +
    +
    +

    See also

    +

    removeBatchEffect

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/remove_batch_effect_cluster_hits.html b/docs/reference/remove_batch_effect_cluster_hits.html new file mode 100644 index 0000000..0a9b182 --- /dev/null +++ b/docs/reference/remove_batch_effect_cluster_hits.html @@ -0,0 +1,164 @@ + +Remove Batch Effect from Cluster Hits — remove_batch_effect_cluster_hits • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Remove Batch Effect from Cluster Hits

    + + +
    + +
    +

    This function removes batch effects from the data for each level specified +by the condition. It supports both isolated and integrated modes, with +optional handling for a second batch column.

    +
    + +
    + 
    remove_batch_effect_cluster_hits(
+  data,
+  meta,
+  condition,
+  meta_batch_column,
+  meta_batch2_column,
+  design,
+  mode,
+  spline_params
+)
    +
    + +
    +

    Arguments

    + + +
    data
    +

    A dataframe containing the main data.

    + + +
    meta
    +

    A dataframe containing meta information.

    + + +
    condition
    +

    A string specifying the column in `meta` that divides the +experiment into levels.

    + + +
    meta_batch_column
    +

    A string specifying the column in `meta` that +indicates batch information.

    + + +
    meta_batch2_column
    +

    A string specifying the second batch column in +`meta`, if applicable.

    + + +
    design
    +

    A design matrix for the experiment.

    + + +
    mode
    +

    A string indicating the mode of operation: "isolated" or +"integrated".

    + + +
    spline_params
    +

    A list of spline parameters for the design matrix.

    + +
    +
    +

    Value

    +

    A list of dataframes with batch effects removed for each level.

    +
    +
    +

    Details

    +

    The function operates in two modes:

    isolated
    +

    Processes each level independently, using only data from + that level.

    + +
    integrated
    +

    Processes the entire dataset together.

    + + +

    If `meta_batch_column` is specified, the function removes batch effects using +`removeBatchEffect`. If a second batch column (`meta_batch2_column`) is +specified, it is also included in the batch effect removal.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/remove_prefix.html b/docs/reference/remove_prefix.html new file mode 100644 index 0000000..5683448 --- /dev/null +++ b/docs/reference/remove_prefix.html @@ -0,0 +1,111 @@ + +Remove Prefix from String — remove_prefix • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Remove Prefix from String

    + + +
    + +
    +

    Removes a specified prefix from the beginning of a string. This function +is useful for cleaning or standardizing strings by removing known prefixes.

    +
    + +
    + 
    remove_prefix(string, prefix)
    +
    + +
    +

    Arguments

    + + +
    string
    +

    A string from which the prefix should be removed.

    + + +
    prefix
    +

    A string representing the prefix to be removed.

    + +
    +
    +

    Value

    +

    A string with the prefix removed.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/run_gsea.html b/docs/reference/run_gsea.html new file mode 100644 index 0000000..b155319 --- /dev/null +++ b/docs/reference/run_gsea.html @@ -0,0 +1,145 @@ + +Generate a GSEA Report — run_gsea • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Generate a GSEA Report

    + + +
    + +
    +

    This function generates a Gene Set Enrichment Analysis (GSEA) report based +on clustered hit levels, gene data, and specified databases. It processes +the input data, manages GSEA levels, and produces an HTML report with plots.

    +
    + +
    + 
    run_gsea(
+  levels_clustered_hits,
+  databases,
+  report_info,
+  clusterProfiler_params = NA,
+  plot_titles = NA,
+  background = NULL,
+  report_dir = here::here()
+)
    +
    + +
    +

    Arguments

    + + +
    levels_clustered_hits
    +

    A list of clustered hits at different levels.

    + + +
    databases
    +

    A list of databases for the gene set enrichment analysis.

    + + +
    report_info
    +

    A list containing information for the report generation.

    + + +
    clusterProfiler_params
    +

    Additional parameters for the GSEA analysis, +default is NA. Those include adj_p_value, +pAdjustMethod, etc (see clusterProfiler +documentation).

    + + +
    plot_titles
    +

    Titles for the plots, default is NA.

    + + +
    background
    +

    Background data, default is NULL.

    + + +
    report_dir
    +

    Directory where the report will be saved, default is +`here::here()`.

    + +
    +
    +

    Value

    +

    A list of plots generated for the GSEA report.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/run_limma_splines.html b/docs/reference/run_limma_splines.html new file mode 100644 index 0000000..e888574 --- /dev/null +++ b/docs/reference/run_limma_splines.html @@ -0,0 +1,131 @@ + +run_limma_splines.R contains the exported package function run_limma_splines and all the functions that make up the functionality of run_limma_splines. run_limma_splines performs a limma analysis, using splines, to assign a p-value to every feature of a time series omics dataset, to find out which features are significantly changed over the time course. Run Limma Analysis with Spline Interpolation for Hyperparameter Screening — run_limma_splines • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    run_limma_splines.R contains the exported package function run_limma_splines and all the functions that make up the functionality of run_limma_splines. run_limma_splines performs a limma analysis, using splines, to assign a p-value to every feature of a time series omics dataset, to find out which features are significantly changed over the time course. Run Limma Analysis with Spline Interpolation for Hyperparameter Screening

    + + +
    + +
    +

    This function conducts differential expression analysis using the Limma +package, +incorporating spline interpolation to model the effect of various +experimental +factors across different levels. It supports both isolated and integrated +modes +for within-level analysis and between-level comparison, adjusting for +multiple +degrees of freedom corresponding to the factors under investigation.

    +
    + +
    + 
    run_limma_splines(splineomics)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    A SplineOmics object, containing data, meta, design, +condition, and spline_params.

    + +
    +
    +

    Value

    +

    The SplineOmics object, updated with a list with three elements: + - `time_effect`: A list of top tables for each level with the time + effect. + - `avrg_diff_conditions`: A list of top tables for each comparison + between the levels. The comparison is the + average difference of the values. + - `interaction_condition_time`: A list of top tables for each + comparison between levels. The + comparison is the interaction between + the condition and the time.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/screen_limma_hyperparams.html b/docs/reference/screen_limma_hyperparams.html new file mode 100644 index 0000000..4d59312 --- /dev/null +++ b/docs/reference/screen_limma_hyperparams.html @@ -0,0 +1,182 @@ + +screen_limma_hyperparams.R contains the exported package function screen_limma_hyperparams and all the functions that make up the functionality of screen_limma_hyperparams. screen_limma_hyperparams runs the other package function, run_limma_splines, for a time series omics dataset, for different hyperparameters. Such are for example degree of freedom of the spline, type of spline, limma design formula, and different versions of the data (full data vs. outliers removed). This can result in several combinations, and it is tedious analyzing the combination in an organised and structured manner. Therefore, this function streamlines that process. Limma Hyperparameters Screening — screen_limma_hyperparams • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    screen_limma_hyperparams.R contains the exported package function screen_limma_hyperparams and all the functions that make up the functionality of screen_limma_hyperparams. screen_limma_hyperparams runs the other package function, run_limma_splines, for a time series omics dataset, for different hyperparameters. Such are for example degree of freedom of the spline, type of spline, limma design formula, and different versions of the data (full data vs. outliers removed). This can result in several combinations, and it is tedious analyzing the combination in an organised and structured manner. Therefore, this function streamlines that process. Limma Hyperparameters Screening

    + + +
    + +
    +

    This function screens through various combinations of hyperparameters for +limma analysis, +including designs, modes, and degrees of freedom. It validates inputs, +generates results for all +combinations, and plots the outcomes. Finally, it may also be involved in +generating an HTML report +as part of a larger analysis workflow.

    +
    + +
    + 
    screen_limma_hyperparams(
+  splineomics,
+  datas,
+  datas_descr,
+  metas,
+  designs,
+  spline_test_configs,
+  report_dir = here::here(),
+  adj_pthresholds = c(0.05),
+  time_unit = "min",
+  padjust_method = "BH"
+)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    An S3 object of class `SplineOmics` that contains all the +necessary data and parameters for the analysis, including:

    • condition: A string specifying the column name of the meta + dataframe, that contains the levels that separate + the experiment ('treatment' can be a condition, and + 'drug' and 'no drug' can be the levels of such a + condition).

      • +

    • report_info:

      • +

    • meta_batch_column: A character string specifying the meta + batch column.

      • +

    • meta_batch2_column: A character string specifying the second + meta batch column (the limma function + removeBatchEffect supports a maximum of + two batch columns.)

      • +
    + + +
    datas
    +

    A list of data frames containing the datasets to be analyzed.

    + + +
    datas_descr
    +

    A description object for the data.

    + + +
    metas
    +

    A list of data frames containing metadata for each dataset in +`datas`.

    + + +
    designs
    +

    A character vector of design formulas for the limma analysis.

    + + +
    spline_test_configs
    +

    A configuration object for spline tests.

    + + +
    report_dir
    +

    A non-empty string specifying the report directory.

    + + +
    adj_pthresholds
    +

    A numeric vector of p-value thresholds for +significance determination.

    + + +
    time_unit
    +

    A character string specifying the time unit label for plots.

    + + +
    padjust_method
    +

    A character string specifying the method for p-value +adjustment.

    + +
    +
    +

    Value

    +

    Returns a list of plots generated from the limma analysis results. + Each element in the list corresponds to a different combination of + hyperparameters.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/set_default_params.html b/docs/reference/set_default_params.html new file mode 100644 index 0000000..ce4fb86 --- /dev/null +++ b/docs/reference/set_default_params.html @@ -0,0 +1,113 @@ + +Set Default Parameters — set_default_params • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Set Default Parameters

    + + +
    + +
    +

    This function checks if the provided `params` list is `NA` or missing any +elements. If `params` is `NA`, it assigns a list of default parameters. +If any element is missing from `params`, it adds the missing element with +its respective default value.

    +
    + +
    + 
    set_default_params(params)
    +
    + +
    +

    Arguments

    + + +
    params
    +

    A list of parameters to be checked and updated with default +values if necessary.

    + +
    +
    +

    Value

    +

    A list of parameters with all required elements, either from the + input `params` or with added default values for any missing elements.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/shorten_names.html b/docs/reference/shorten_names.html new file mode 100644 index 0000000..361f6fe --- /dev/null +++ b/docs/reference/shorten_names.html @@ -0,0 +1,114 @@ + +Shorten Names — shorten_names • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Shorten Names

    + + +
    + +
    +

    Replaces occurrences of unique values within a name with their first three +characters. This function is useful for abbreviating long condition names +in a dataset.

    +
    + +
    + 
    shorten_names(name, unique_values)
    +
    + +
    +

    Arguments

    + + +
    name
    +

    A string representing the name to be shortened.

    + + +
    unique_values
    +

    A vector of unique values whose abbreviations will +replace their occurrences in the name.

    + +
    +
    +

    Value

    +

    A string with the unique values replaced by their abbreviations.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/store_hits.html b/docs/reference/store_hits.html new file mode 100644 index 0000000..97e0123 --- /dev/null +++ b/docs/reference/store_hits.html @@ -0,0 +1,109 @@ + +Store Hits — store_hits • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Store Hits

    + + +
    + +
    +

    Stores the feature indices for significant hits based on the adjusted p-value +threshold for each condition.

    +
    + +
    + 
    store_hits(condition)
    +
    + +
    +

    Arguments

    + + +
    condition
    +

    A list containing dataframes and parameters for each +condition.

    + +
    +
    +

    Value

    +

    A list where each element is a vector of feature indices that meet +the significance threshold.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/truncate_row_names.html b/docs/reference/truncate_row_names.html new file mode 100644 index 0000000..e39167e --- /dev/null +++ b/docs/reference/truncate_row_names.html @@ -0,0 +1,114 @@ + +Truncate Row Names — truncate_row_names • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Truncate Row Names

    + + +
    + +
    +

    This function truncates row names that exceed a specified maximum length. +If the row name length exceeds the maximum length, it appends " ..." +to indicate truncation.

    +
    + +
    + 
    truncate_row_names(names, max_length = 40)
    +
    + +
    +

    Arguments

    + + +
    names
    +

    A character vector of row names.

    + + +
    max_length
    +

    An integer specifying the maximum length of the row names. +Default is 40.

    + +
    +
    +

    Value

    +

    A character vector of truncated row names.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/update_splineomics.html b/docs/reference/update_splineomics.html new file mode 100644 index 0000000..54069fe --- /dev/null +++ b/docs/reference/update_splineomics.html @@ -0,0 +1,109 @@ + +Update a SplineOmics object — update_splineomics • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Update a SplineOmics object

    + + +
    + +
    +

    Updates a SplineOmics object by modifying existing fields or adding new ones.

    +
    + +
    + 
    update_splineomics(splineomics, ...)
    +
    + +
    +

    Arguments

    + + +
    splineomics
    +

    A SplineOmics object to be updated.

    + + +
    ...
    +

    Named arguments with new values for fields to be updated or added.

    + +
    +
    +

    Value

    +

    The updated SplineOmics object.

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/reference/within_level.html b/docs/reference/within_level.html new file mode 100644 index 0000000..7f52ec2 --- /dev/null +++ b/docs/reference/within_level.html @@ -0,0 +1,170 @@ + +Within level analysis — within_level • SplineOmics + + +
    +
    + + + +
    +
    +
    +

    Within level analysis

    + + +
    + +
    +

    Processes a single level within a condition, performing LIMMA analysis +and generating the top table of results.

    +
    + +
    + 
    within_level(
+  level,
+  level_index,
+  spline_params,
+  data,
+  preprocess_rna_seq,
+  normalization_fun,
+  meta,
+  design,
+  condition,
+  feature_names,
+  padjust_method,
+  mode
+)
    +
    + +
    +

    Arguments

    + + +
    level
    +

    The level within the condition to process.

    + + +
    level_index
    +

    The index of the level within the condition.

    + + +
    spline_params
    +

    A list of spline parameters for the analysis.

    + + +
    data
    +

    A matrix of data values.

    + + +
    preprocess_rna_seq
    +

    Boolean specifying whether to preprocess RNA seq

    + + +
    normalization_fun
    +

    Function to normalize RNA-seq raw counts.

    + + +
    meta
    +

    A dataframe containing metadata.

    + + +
    design
    +

    A design formula or matrix for the LIMMA analysis.

    + + +
    condition
    +

    A character string specifying the condition.

    + + +
    feature_names
    +

    A non-empty character vector of feature names.

    + + +
    padjust_method
    +

    A character string specifying the p-adjustment method.

    + + +
    mode
    +

    A character string specifying the mode +('isolated' or 'integrated').

    + +
    +
    +

    Value

    +

    A list containing the name of the results and the top table of + results.

    +
    +
    +

    See also

    +

    within_level, process_top_table

    +
    + +
    + +
    + + +
    +

    Developed by Thomas Rauter.

    +
    + +
    +

    Site built with pkgdown 2.1.0.

    +
    + +
    + + + + + + + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 6166980..b7667cc 100755 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -1,375 +1,144 @@ - - - - /404.html - - - /CODE_OF_CONDUCT.html - - - /LICENSE-text.html - - - /articles/Docker_permission_denied.html - - - /articles/functions-in-depth.html - - - /articles/get-started.html - - - /articles/index.html - - - /authors.html - - - /example_report.html - - - /index.html - - - /reference/InputControl.html - - - /reference/Level2Functions.html - - - /reference/Level3Functions.html - - - /reference/Level4Functions.html - - - /reference/NumericBlockFinder.html - - - /reference/SplineOmics-package.html - - - /reference/add_feature_names.html - - - /reference/between_level.html - - - /reference/build_cluster_hits_report.html - - - /reference/build_create_gsea_report.html - - - /reference/build_create_limma_report.html - - - /reference/build_explore_data_report.html - - - /reference/build_hyperparams_screen_report.html - - - /reference/check_clustered_hits.html - - - /reference/check_databases.html - - - /reference/check_datas_descr.html - - - /reference/check_genes.html - - - /reference/check_null_elements.html - - - /reference/check_params.html - - - /reference/check_spline_test_configs.html - - - /reference/cluster_hits.html - - - /reference/control_inputs_create_gsea_report.html - - - /reference/control_inputs_extract_data.html - - - /reference/control_inputs_run_limma.html - - - /reference/create_gsea_report.html - - - /reference/create_gsea_report_level.html - - - /reference/create_limma_report.html - - - /reference/create_p_value_histogram.html - - - /reference/create_progress_bar.html - - - /reference/create_spline_params.html - - - /reference/create_toc.html - - - /reference/create_volcano_plot.html - - - /reference/dbs_to_term2genes.html - - - /reference/define_html_styles.html - - - /reference/design2design_matrix.html - - - /reference/determine_analysis_mode.html - - - /reference/download_enrichr_databases.html - - - /reference/encode_df_to_base64.html - - - /reference/enrichr_get_genesets.html - - - /reference/explore_data.html - - - /reference/extract_data.html - - - /reference/flatten_spline_configs.html - - - /reference/format_text.html - - - /reference/gen_composite_spline_plots.html - - - /reference/gen_hitcomp_plots.html - - - /reference/generate_avrg_diff_plots.html - - - /reference/generate_explore_plots.html - - - /reference/generate_interaction_plots.html - - - /reference/generate_report_html.html - - - /reference/generate_report_html_new.html - - - /reference/generate_reports.html - - - /reference/generate_reports_meta.html - - - /reference/generate_section_content.html - - - /reference/generate_time_effect_plots.html - - - /reference/get_curve_values.html - - - /reference/get_explore_plots_explanations.html - - - /reference/get_header_section.html - - - /reference/get_limma_combos_results.html - - - /reference/get_spline_params_info.html - - - /reference/hc_add.html - - - /reference/hc_barplot.html - - - /reference/hc_new.html - - - /reference/hc_vennheatmap.html - - - /reference/hierarchical_clustering.html - - - /reference/huge_table_user_prompter.html - - - /reference/index.html - - - /reference/is_not_na.html - - - /reference/limma_hyperparams_screen.html - - - /reference/make_box_plots.html - - - /reference/make_clustering_report.html - - - /reference/make_correlation_heatmaps.html - - - /reference/make_density_plots.html - - - /reference/make_enrich_dotplot.html - - - /reference/make_mds_plot.html - - - /reference/make_pca_plot.html - - - /reference/make_scree_plot.html - - - /reference/make_tsne_plot.html - - - /reference/make_violin_plots.html - - - /reference/manage_gsea_level.html - - - /reference/modify_limma_top_table.html - - - /reference/normalize_curves.html - - - /reference/perform_clustering.html - - - /reference/plot2base64.html - - - /reference/plot_all_shapes.html - - - /reference/plot_composite_splines.html - - - /reference/plot_consensus_shapes.html - - - /reference/plot_cv.html - - - /reference/plot_dendrogram.html - - - /reference/plot_first_lag_autocorrelation.html - - - /reference/plot_heatmap.html - - - /reference/plot_lag1_differences.html - - - /reference/plot_limma_combos_results.html - - - /reference/plot_mean_correlation_with_time.html - - - /reference/plot_single_and_consensus_splines.html - - - /reference/plot_splines.html - - - /reference/prepare_plot_data.html - - - /reference/process_combo.html - - - /reference/process_combo_pair.html - - - /reference/process_config_column.html - - - /reference/process_data.html - - - /reference/process_enrichment_results.html - - - /reference/process_level_cluster.html - - - /reference/process_plots.html - - - /reference/process_result.html - - - /reference/process_top_table.html - - - /reference/process_within_level.html - - - /reference/remove_batch_effect.html - - - /reference/remove_prefix.html - - - /reference/run_limma_splines.html - - - /reference/screen_limma_hyperparams.html - - - /reference/set_default_params.html - - - /reference/shorten_names.html - - - /reference/store_hits.html - - - /reference/within_level.html - + +/404.html +/CODE_OF_CONDUCT.html +/LICENSE-text.html +/articles/Docker-instructions.html +/articles/Docker_permission_denied.html +/articles/design_limma_design_formula.html +/articles/functions-in-depth.html +/articles/get-started.html +/articles/index.html +/authors.html +/example_report.html +/get-started.html +/index.html +/reference/InputControl.html +/reference/Level2Functions.html +/reference/Level3Functions.html +/reference/Level4Functions.html +/reference/NumericBlockFinder.html +/reference/SplineOmics-package.html +/reference/add_feature_names.html +/reference/add_plot_to_html.html +/reference/ask_user.html +/reference/between_level.html +/reference/bind_data_with_annotation.html +/reference/build_cluster_hits_report.html +/reference/build_create_gsea_report.html +/reference/build_create_limma_report.html +/reference/build_explore_data_report.html +/reference/build_hyperparams_screen_report.html +/reference/check_between_level_pattern.html +/reference/check_clustered_hits.html +/reference/check_databases.html +/reference/check_genes.html +/reference/check_null_elements.html +/reference/check_params.html +/reference/check_splineomics_elements.html +/reference/clean_gene_symbols.html +/reference/cluster_hits.html +/reference/control_inputs_create_gsea_report.html +/reference/control_inputs_extract_data.html +/reference/create_enrichr_zip.html +/reference/create_gsea_report_level.html +/reference/create_limma_report.html +/reference/create_p_value_histogram.html +/reference/create_progress_bar.html +/reference/create_spline_params.html +/reference/create_splineomics.html +/reference/create_toc.html +/reference/create_volcano_plot.html +/reference/dbs_to_term2genes.html +/reference/define_html_styles.html 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+/reference/remove_batch_effect.html +/reference/remove_batch_effect_cluster_hits.html +/reference/remove_prefix.html +/reference/run_gsea.html +/reference/run_limma_splines.html +/reference/screen_limma_hyperparams.html +/reference/set_default_params.html +/reference/shorten_names.html +/reference/store_hits.html +/reference/truncate_row_names.html +/reference/update_splineomics.html +/reference/within_level.html + diff --git a/vignettes/Docker_permission_denied.Rmd b/vignettes/Docker_permission_denied.Rmd index b8cf878..509b89a 100755 --- a/vignettes/Docker_permission_denied.Rmd +++ b/vignettes/Docker_permission_denied.Rmd @@ -4,7 +4,7 @@ author: "Thomas Rauter" date: "10 June, 2024" output: rmarkdown::html_vignette vignette: > - %\VignetteIndexEntry{Docker-permission-denied} + %\VignetteIndexEntry{Docker_permission_denied} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} ---