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Merge pull request #321 from ncborcherding/dev
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Update pkgdown page
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ncborcherding authored Feb 24, 2024
2 parents e51695a + 427f525 commit 6a919b9
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2 changes: 1 addition & 1 deletion NEWS.md
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Expand Up @@ -27,7 +27,7 @@
* **.theCall()** now allows for a custom header/variable and checks the colnames.
* Replaced data arguments to be more descriptive: *df* is now *input.data*, *dir* is now *input*, and *sc* is now *sc.data*
* Deep clean on the documentation for each function for increased consistency and explainability
* ```Startracdiversity()``` metric re-implemented to remove startrac-class object intermediary
* ```StartracDiversity()``` metric re-implemented to remove startrac-class object intermediary
* Implemented powerTCR locally to reduce dependencies and continue support
* Universalized underlying function language and intermediate variables
* License change to MIT
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2 changes: 1 addition & 1 deletion R/positionalProperty.R
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Expand Up @@ -67,7 +67,7 @@ positionalProperty <- function(input.data,
input.data <- .groupList(input.data, group.by)
}

#Selecting Diversit Function
#Selecting Property Function
propertyFunc <- switch(method,
"Atchley" = .af.ref,
"Kidera" = .kf.ref,
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -29,7 +29,7 @@ devtools::install_github("ncborcherding/scRepertoire")
```

### Installing from Bioconductor
The current version of scRepertoire is also available in the development version of Bioconductor. Important to note, the version is listed as 1.99.0 on [Bioconductor](https://bioconductor.org/packages/3.19/bioc/html/scRepertoire.html) per their version guidelines.
The current version of scRepertoire is also available in the development version of Bioconductor. Important to note, the version is listed as 1.99.1 on [Bioconductor](https://bioconductor.org/packages/3.19/bioc/html/scRepertoire.html) per their version guidelines.

```R
BiocManager::install(version='devel')
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3 changes: 3 additions & 0 deletions _pkgdown.yml
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Expand Up @@ -51,6 +51,8 @@ navbar:
href: articles/Trex.html
- text: Combining Deep Learning and BCRs with Ibex
href: articles/Ibex.html
- text: Single-cell Gene Set Enrichment Analysis
href: articles/Running_Escape.html
- text: News/Changelog
href: news/index.html
- text: Reference
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- contents:
- percentAA
- positionalEntropy
- positionalProperty
- percentGenes
- percentKmer
- percentVJ
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3 changes: 2 additions & 1 deletion inst/pkgdown.yml
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Expand Up @@ -15,9 +15,10 @@ articles:
Loading: Loading.html
Processing: Processing.html
Repertoire_Summary: Repertoire_Summary.html
Running_Escape: Running_Escape.html
SC_Visualizations: SC_Visualizations.html
Trex: Trex.html
last_built: 2024-01-22T10:54Z
last_built: 2024-02-24T16:17Z
urls:
reference: https://www.borch.dev/uploads/scRepertoire/reference
article: https://www.borch.dev/uploads/scRepertoire/articles
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2 changes: 0 additions & 2 deletions vignettes/articles/Attaching_SC.Rmd
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Expand Up @@ -45,8 +45,6 @@ data("contig_list")
combined.TCR <- combineTCR(contig_list,
samples = c("P17B", "P17L", "P18B", "P18L",
"P19B","P19L", "P20B", "P20L"))
googledrive::drive_download("https://drive.google.com/file/d/1_YuRraDyg8UgF3oasjF0-jgPnwox-B24/view?usp=share_link", overwrite = TRUE)
```

The data in the scRepertoire package is derived from a [study](https://pubmed.ncbi.nlm.nih.gov/33622974/) of acute respiratory stress disorder in the context of bacterial and COVID-19 infections. The internal single cell data (`scRep_example()`) built in to scRepertoire is randomly sampled 500 cells from the fully integrated Seurat object to minimize the package size. However, for the purpose of the vignette we will use the full single-cell object with 30,000 cells. We will use both Seurat and Single-Cell Experiment (SCE) with scater to perform further visualizations in tandem.
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4 changes: 1 addition & 3 deletions vignettes/articles/Clonal_Cluster.Rmd
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Expand Up @@ -42,9 +42,7 @@ suppressMessages(library(Seurat))
data("contig_list")
combined.TCR <- combineTCR(contig_list,
samples = c("P17B", "P17L", "P18B", "P18L",
"P19B","P19L", "P20B", "P20L"))
googledrive::drive_download("https://drive.google.com/file/d/1_YuRraDyg8UgF3oasjF0-jgPnwox-B24/view?usp=share_link", overwrite = TRUE)
"P19B","P19L", "P20B", "P20L"))
scRep_example <- readRDS("scRep_example_full.rds")
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2 changes: 1 addition & 1 deletion vignettes/articles/Ibex.Rmd
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Expand Up @@ -37,7 +37,7 @@ knitr::opts_chunk$set(
time_it = TRUE
)
suppressMessages(library(reticulate))
use_condaenv(condaenv = "r-reticulate", required = TRUE)
#use_condaenv(condaenv = "r-reticulate", required = TRUE)
suppressMessages(library(Ibex))
suppressMessages(library(Seurat))
suppressMessages(library(ggplot2))
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4 changes: 2 additions & 2 deletions vignettes/articles/Installation.Rmd
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Expand Up @@ -55,9 +55,9 @@ remotes::install_github(repo = "ncborcherding/scRepertoire", ref = "dev")

## Bioconductor

The current version of scRepertoire is also available in the development version of Bioconductor. Important to note, the version is listed as 1.99.0 on [Bioconductor](https://bioconductor.org/packages/3.19/bioc/html/scRepertoire.html) per their version guidelines.
The current version of scRepertoire is also available in the development version of Bioconductor. Important to note, the version is listed as 1.99.1 on [Bioconductor](https://bioconductor.org/packages/3.19/bioc/html/scRepertoire.html) per their version guidelines.

```{r}
```
BiocManager::install(version='devel')
BiocManager::install("scRepertoire")
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