This reproducible R Markdown analysis was created with workflowr (version 1.6.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
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The results in this page were generated with repository version 7d637d3. 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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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.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.
This is my online notebook to document and share the full results of whole-genome integrated analyses of 38 gene regulatory networks and 18 human complex traits described in the following research article:
Xiang Zhu, Zhana Duren, Wing Hung Wong (2020). Modeling regulatory network topology improves genome-wide analyses of complex human traits. bioRxiv. https://doi.org/10.1101/2020.03.13.990010.
If you find the analysis results, the pre-processed networks, the statistical methods, and/or the open-source software useful for your work, please kindly cite the research article listed above, Zhu et al (2020).
If you have any question about the notebook and/or the article, please feel free to contact me: Xiang Zhu, xiangzhu[at]stanford.edu.
Main results
For each phenotype below, please click to view network enrichment results, click to view gene prioritization results, and click to view gene cross-reference results. Please note that loading pages of gene prioritization results may take a while because of the large number of genes displayed.
Overview
Main results
to view network enrichment results, click 
to view gene prioritization results, and click 
to view gene cross-reference results. Please note that loading pages of gene prioritization results may take a while because of the large number of genes displayed.
Additional resources