merge main

.github/workflows/README.md

@@ -2,7 +2,7 @@
 
 This directory contains workflows to be used for Lessons using the {sandpaper}
 lesson infrastructure. Two of these workflows require R (`sandpaper-main.yaml`
-and `pr-recieve.yaml`) and the rest are bots to handle pull request management.
+and `pr-receive.yaml`) and the rest are bots to handle pull request management.
 
 These workflows will likely change as {sandpaper} evolves, so it is important to
 keep them up-to-date. To do this in your lesson you can do the following in your
@@ -94,9 +94,9 @@ branch called `update/workflows` and a pull request is created. Maintainers are
 encouraged to review the changes and accept the pull request if the outputs
 are okay.
 
-This update is run ~~weekly or~~ on demand.
+This update is run weekly or on demand.
 
-### 03 Maintain: Update Pacakge Cache (update-cache.yaml)
+### 03 Maintain: Update Package Cache (update-cache.yaml)
 
 For lessons that have generated content, we use {renv} to ensure that the output
 is stable. This is controlled by a single lockfile which documents the packages
@@ -140,7 +140,7 @@ Once the checks are finished, a comment is issued to the pull request, which
 will allow maintainers to determine if it is safe to run the 
 "Receive Pull Request" workflow from new contributors.
 
-### Recieve Pull Request (pr-recieve.yaml)
+### Receive Pull Request (pr-receive.yaml)
 
 **Note of caution:** This workflow runs arbitrary code by anyone who creates a
 pull request. GitHub has safeguarded the token used in this workflow to have no
@@ -171,7 +171,7 @@ The artifacts produced are used by the next workflow.
 
 ### Comment on Pull Request (pr-comment.yaml)
 
-This workflow is triggered if the `pr-recieve.yaml` workflow is successful.
+This workflow is triggered if the `pr-receive.yaml` workflow is successful.
 The steps in this workflow are:
 
 1. Test if the workflow is valid and comment the validity of the workflow to the

.github/workflows/sandpaper-version.txt

@@ -1 +1 @@
-0.12.4
+0.16.5

episodes/25-starting-with-data.Rmd

@@ -56,7 +56,7 @@ columns represent:
 | age        | The age of the mouse (all mice were 8 weeks here)                                            |
 | sex        | The sex of the mouse                                                                         |
 | infection  | The infection state of the mouse, i.e. infected with Influenza A or not infected.            |
-| strain     | The Influenza A strain; C57BL/6 in all cases.                                                |
+| strain     | The Influenza A strain.                                                                      |
 | time       | The duration of the infection (in days).                                                     |
 | tissue     | The tissue that was used for the gene expression experiment, i.e. cerebellum or spinal cord. |
 | mouse      | The mouse unique identifier.                                                                 |
@@ -206,8 +206,6 @@ questions?
 - class: data frame
 - how many rows: 32428, how many columns: 19
 
-
-
 :::::::::::::::::::::::::
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::

episodes/30-dplyr.Rmd

@@ -11,8 +11,11 @@ exercises: 75
 ::::::::::::::::::::::::::::::::::::::: objectives
 
 - Describe the purpose of the **`dplyr`** and **`tidyr`** packages.
-- Describe several of their functions that are extremely useful to manipulate data.
-- Describe the concept of a wide and a long table format, and see how to reshape a data frame from one format to the other one.
+- Describe several of their functions that are extremely useful to 
+  manipulate data.
+- Describe the concept of a wide and a long table format, and see 
+  how to reshape a data frame from one format to the other one.
+- Demonstrate how to join tables. 
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 
@@ -24,7 +27,7 @@ exercises: 75
 
 ```{r loaddata_dplyr, echo=FALSE, purl=FALSE, message=FALSE}
 if (!file.exists("data/rnaseq.csv"))
-download.file(url = "https://github.com/Bioconductor/bioconductor-teaching/raw/master/data/GSE96870/rnaseq.csv",
+download.file(url = "https://github.com/carpentries-incubator/bioc-intro/raw/main/episodes/data/rnaseq.csv",
               destfile = "data/rnaseq.csv")
 ```
 
@@ -511,7 +514,6 @@ rna %>%
 ## 3.
 rna %>%
   filter(sample == "GSM2545336") %>%
-  group_by(gene_biotype) %>%
   count(gene_biotype) %>%
   arrange(desc(n))
 ## 4.
@@ -612,16 +614,13 @@ Let's imagine that for some reason, we had some missing expression values for so
 genes in certain samples. In the following fictive example, the gene Cyp2d22 has only
 one expression value, in GSM2545338 sample.
 
-```{r, purl=TRUE, echo=FALSE}
+```{r, purl=TRUE}
 rna_with_missing_values <- rna %>%
   select(gene, sample, expression) %>%
   filter(gene %in% c("Asl", "Apod", "Cyp2d22")) %>%
   filter(sample %in% c("GSM2545336", "GSM2545337", "GSM2545338")) %>%
   arrange(sample) %>%
   filter(!(gene == "Cyp2d22" & sample != "GSM2545338"))
-```
-
-```{r, purl=TRUE}
 rna_with_missing_values
 ```
 

episodes/40-visualization.Rmd

@@ -7,7 +7,7 @@ exercises: 60
 
 ```{r loaddata_vis, echo=FALSE, purl=FALSE, message=FALSE}
 if (!file.exists("data/rnaseq.csv"))
-download.file(url = "https://raw.githubusercontent.com/Bioconductor/bioconductor-teaching/master/data/GSE96870/rnaseq.csv",
+download.file(url = "https://github.com/carpentries-incubator/bioc-intro/raw/main/episodes/data/rnaseq.csv",
               destfile = "data/rnaseq.csv")
 ```
 

learners/setup.md

@@ -158,7 +158,6 @@ commands. For now, simply follow the instructions below:
 
 ```r
 install.packages(c("BiocManager", "remotes"))
-BiocManager::install(c("tidyverse", "SummarizedExperiment",
-                       "UCLouvain-CBIO/rWSBIM1207", "hexbin",
+BiocManager::install(c("tidyverse", "SummarizedExperiment", "hexbin",
                        "patchwork", "gridExtra", "lubridate"))
 ```