Last updated: 2022-04-25
Checks: 2 0
Knit directory: synovialscrnaseq/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 3443cc6. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
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Unstaged changes:
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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/about.Rmd) and HTML (public/about.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 3443cc6 | Reto Gerber | 2022-04-25 | Update |
| Rmd | e88c23e | Reto Gerber | 2021-07-12 | add ambient RNA analysis |
| html | e88c23e | Reto Gerber | 2021-07-12 | add ambient RNA analysis |
| html | a28e4c4 | retogerber | 2021-01-29 | update website |
| html | 04c48dc | retogerber | 2021-01-29 | add main website files |
| Rmd | 0e7eabd | retogerber | 2021-01-05 | Start workflowr project. |
The complete analysis was run using singularity. Install instructions can be found here. To recreate the analysis first download the container:
singularity pull library://retogerber/default/bioc_python_synovial_v2.sifand then run the following (adjustments needed, read below)
R_LIBS_USER='/usr/local/lib/R/site-library,/usr/local/lib/R/library'
export R_LIBS_USER
SINGULARITY_BIND='PROJECT_DIR:PROJECT_DIR,RAWDATA_DIR/data:PROJECT_DIR/data_server,TMP_DIR/tmp:TMP_DIR/tmp,TMP_DIR/run:/run'
export SINGULARITY_BIND
singularity exec bioc_python_synovial_v2.sif R -e "workflowr::wflow_build()"where R_LIBS_USER makes sure that only R libraries within the container are used and SINGULARITY_BIND makes all the binds between the host and the container. Replace PROJECT_DIR with the directory of the project (e.g. ~/protocol_synovial) and RAWDATA_DIR with the directory of the raw data, which contains a directory called data containing the raw data. TMP_DIR is a temporary directory to allow R to function properly and needs two directories within, tmp and run. Those can be created with mkdir -p TMP_DIR/{tmp,run}.
To run individual scripts run
singularity exec bioc_python_synovial_v2.sif R -e "workflowr::wflow_build(SCRIPT_NAME)"replacing SCRIPT_NAME with the name of the script to run.
To speed the analysis up the number of cores was set between 10-20, if you want to change that number adjust the variable n_workers at the top within each script keeping in mind that this might influence the results slightly (random seed).
The Singularity build file (for the image) can be found here.