Last updated: 2018-10-05

workflowr checks: (Click a bullet for more information)

• ✔ R Markdown file: up-to-date

  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.

• ✔ Repository version: 7333082

  Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.
  
  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:

  
  Ignored files:
      Ignored:    .Rhistory
      Ignored:    .Rproj.user/
  
  

  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.

Expand here to see past versions:

File	Version	Author	Date	Message
html	ff6afd0	Xiang Zhu	2018-06-26	Build site.
Rmd	bf31edf	Xiang Zhu	2018-06-26	wflow_publish(files = c(“analysis/index.Rmd”, “analysis/license.Rmd”))
Rmd	cee1a92	Xiang Zhu	2018-06-26	Start workflowr project.

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Currently the project website is licensed under the Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0). This means you are free to include content from this site in your presentation, blog, or social media posts, as long you cite it. The “no derivatives” (ND) clause means you cannot modify the results and distribute them. Once the results are published (manuscript under review), I will remove “no derivatives” clause.

The source code in the notebook is licensed under the GNU General Public License, version 3.0 (GPLv3).

If you use any results from this site, please explicitly acknowledge that the results are retrieved from https://github.com/xiangzhu/rss-gsea, and cite the following preprint:

Xiang Zhu and Matthew Stephens (2017). A large-scale genome-wide enrichment analysis identifies new trait-associated genes, pathways and tissues across 31 human phenotypes. bioRxiv. https://doi.org/10.1101/160770.

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This reproducible R Markdown analysis was created with workflowr 1.1.1

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