fhdsl · cansavvy · Aug 21, 2024 · Aug 21, 2024 · Aug 21, 2024 · Aug 21, 2024
diff --git a/.github/workflows/pull_request.yml b/.github/workflows/pull_request.yml
@@ -16,6 +16,7 @@ jobs:
         uses: actions/checkout@v4
         with:
           fetch-depth: 0
+          token: ${{ secrets.GH_PAT }}
 
         # Use the yaml-env-action action.
       - name: Load environment from YAML
@@ -115,16 +116,16 @@ jobs:
       - name: Website preview for download
         run: zip website-preview.zip docs/* -r
 
-      # Commit the rendered website files
-      - name: Commit rendered website files to preview branch
+      # Commit the rendered bookdown files
+      - name: Commit rendered bookdown files to preview branch
         id: commit
         run: |
           branch_name='preview-${{ github.event.pull_request.number }}'
-          git diff origin/main -- '*.html' >/dev/null && changes=true || changes=false
+          git diff origin/main -- docs >/dev/null && changes=true || changes=false
           echo "changes=$changes" >> $GITHUB_OUTPUT
           git add . --force
           git commit -m 'Render preview' || echo "No changes to commit"
-          git pull --set-upstream origin $branch_name --allow-unrelated-histories --strategy-option=ours
+          git pull --rebase --set-upstream origin $branch_name --allow-unrelated-histories --strategy-option=ours
           git push --force || echo "No changes to commit"
         shell: bash
 

diff --git a/activity.Rmd b/activity.Rmd
@@ -7,7 +7,7 @@ output: html_document
 
 Our Galaxy activity is a condensed tutorial based on the ["Reference-based RNA-Seq data analysis"](https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html) Galaxy Training Tutorial. 
 
-It uses [data that is deposited on and available from zenodo](https://zenodo.org/records/6457007), including subsampled data that will be quicker to work with. 
+It uses [data that is deposited on and available from zenodo](https://zenodo.org/records/6457007), including subsampled data that will be quicker to work with. For more info on the data, checkout the tutorial linked above.
 
 # Activity steps
 
@@ -219,7 +219,7 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8j
 ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_77")
 ```
 
-- [ ] If the "Raw read data from your current history doesn't automatically fill with the renamed output from the Flatten collection tool, select that dataset as input. 
+- [ ] If the "Raw read data" from your current history doesn't automatically fill with the renamed output from the Flatten collection tool, select that dataset as input. 
 
 ```{r echo=FALSE}
 ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_82")
@@ -243,7 +243,6 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8j
 ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_97")
 ```
 
-
 - [ ] In the FastQC output section, click the `+ Insert FastQC output` button. 
 
 ```{r echo=FALSE}
@@ -256,17 +255,111 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8j
 ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_104")
 ```
 
- - [ ] Then with the down arrow, select the `FASTQC on collection __: RawData` data set
+- [ ] Then with the down arrow, select the `FASTQC on collection __: RawData` data set
 
 ```{r echo=FALSE}
 ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_112") 
 ```
+
+- [ ] Optionally, you can add a Report title near the bottom of the middle pane
+
+- [ ] Click the blue Run tool button in the upper right of the middle pane
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_116")
+```
+
+- [ ] Let's open and inspect the webpage output at the top of the history pane. To view the output file, click the eye icon. To download the output, click the save/floppy disc icon. 
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_126")
+```
 
 ### Cutadapt / Trim adaptors
 
-## Mapping
+- [ ] On the top left of the page, using the tool pane search bar, type `Cut` into the search bar and select the `Cutadapt` tool. This will open the `Cutadapt` tool in the middle pane.  
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_121")
+```
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_133")
+```
+
+- [ ]  For `Single-end or Paired-end reads?` click the down arrow and select `Paired-end Collection`. 
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_137")
+```
+
+- [ ]  Verify that it selected your `2 PE fastqs` as the paired collection input, if not, select it.
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_141")
+```
+
+- [ ] Scroll down to the `Other Read Trimming Options` section and edit the `Quality cutoff(s) (R1)*` parameter. Enter a value of 20.
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_146")
+```
+
+- [ ]  Scroll down to the `Read Filtering Options` section and edit the `Minimum length (R1)` parameter. Enter a value of 20.
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_156")
+```
+
+- [ ] Scroll down to the `Additional outputs to generate` checkbox section and check the `Report: Cutadapt's per-adapter statistics. You can use this file with MultiQC`
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_160")
+```
+
+- [ ] Click the blue Run tool button
+
+### View Cutadapt results with MultiQC
+
+- [ ] On the top left of the page, using the tool pane search bar, type `multi` into the search bar and select the `MultiQC` tool. This will open the `MultiQC` tool in the middle pane.  
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_88")
+```
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_93")
+```
+
+- [ ] Within the `Results` section and `Which tool was used to generate logs` subsection, click the down arrow and select `Cutadapt/Trim Galore!`. 
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_168")
+
+```
+
+- [ ] In the blue banner highlighted section, select the file folder "Dataset collection" icon & then with the down arrow, select the `Cutadapt on collection __: Report` data set 
+
+```{r echo=FALSE}
+ottrpal::include_slide("https://docs.google.com/presentation/d/1kWsS23lOJxfbhE8jSdE92JWnEceUEYm5xovCczPbe-8/edit#slide=id.g281646704fe_0_172")
+```
+
+- [ ] We can explore this output as well to see how much of the data was trimmed
+
+## Next steps: Mapping with RNA STAR
+
+Follow the steps in the [Galaxy walkthrough to continue with mapping](https://training.galaxyproject.org/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html#mapping)
+
+## Additional Resources 
+
+Here are some other relevant tutorials from Galaxy:
+
+### Bulk-RNA Seq 
+
+[RNA-Seq Reads to Counts](https://usegalaxy.org/training-material/topics/transcriptomics/tutorials/rna-seq-reads-to-counts/tutorial.html#1-rna-seq-reads-to-counts)
 
-### Run STAR
+[RNA-Seq Counts to Genes (differentially expressed genes)](https://usegalaxy.org/training-material/topics/transcriptomics/tutorials/rna-seq-counts-to-genes/tutorial.html)
 
-### MultiQC to combine log output from STAR 
+[RNA-Seq Genes to Pathways (GSEA)](https://usegalaxy.org/training-material/topics/transcriptomics/tutorials/rna-seq-genes-to-pathways/tutorial.html)
 
+[Tutorials for Visualizing RNA-seq Results](https://usegalaxy.org/training-material/topics/transcriptomics/tutorials/rna-seq-genes-to-pathways/tutorial.html)
diff --git a/index.Rmd b/index.Rmd
@@ -18,7 +18,7 @@ There are 3 workshops throughout the day, each covering one of the following top
 1. [What is gene expression data?](https://hutchdatascience.org/nyu2024-galaxy-activity/gene_expression_workshop.html)<br/>
 10am - 11:30am -- Session led by Candace Savonen and Kate Isaac<br/><br/>
 2. [What are cloud computing resources and how can you use them, specifically Galaxy?](https://hutchdatascience.org/nyu2024-galaxy-activity/computing_workshop.html)<br/>
-12pm - 1:30pm -- Session led by Carrie Wright and Kate Isaac<br/><br/>
+12pm - 1:30pm -- Session led by Carrie Wright and Kate Isaac with an [Intro to using Galaxy for a gene expression analysis actvity](https://hutchdatascience.org/nyu2024-galaxy-activity/activity.html)<br/><br/>
 3. [How is AI useful for scientific research and how do you use it responsibly?](https://hutchdatascience.org/nyu2024-galaxy-activity/ai_workshop.html)<br/>
 1:45pm - 3pm -- Session led by Carrie Wright and Candace Savonen<br/><br/>