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Code for the paper: Genome-wide association study of REM sleep behavior disorder identifies novel loci with distinct polygenic and brain expression effects

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Background

This repository contains scripts used to perform a colocalisation analysis using the REM sleep behavior disorder (RBD) GWAS and two eQTL datasets:

Citation

If you use any of the code or data from this repository, please cite our paper. Further, if you use any of the software used within this repository (e.g. coloc, colochelpR, etc.) please make sure to cite the software appropriately.

License

The code in this repository is released under an MIT license. This repository is distributed in the hope that it will be useful to the wider community, but without any warranty of any kind. Please see the LICENSE file for more details.

Code contents

Scripts and results of analyses have been described in the following workflows:

  1. RBD_coloc.Rmd: Rmd detailing coloc set up and analysis of results.
  2. RBD_coloc_tissue_cell_specificity.Rmd: Rmd detailing tissue- and cell-type-specificity of genes identified by coloc.
  3. RBD_manuscript_figures: Rmd detailing code used to produce manuscript figures pertaining to coloc analyses.

All can be view interactively at: https://rhreynolds.github.io/RBD-GWAS-analysis/

Within this repository you will otherwise find:

Directory Description
docs Contains all .Rmds and their corresponding .htmls describing analyses performed for this project. These can be view interactively at: https://rhreynolds.github.io/RBD-GWAS-analysis/
logs For any scripts that were run outside of an .Rmd (e.g. scripts from the scripts directory), a log file was recorded and can be accessed here.
manuscript Figures and tables produced for the manuscript.
results Results from all analyses.
scripts Contains analysis scripts. Each script contains a one-line description and is also referenced in its corresponding .Rmd.
R Various functions called in docs and scripts.

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Code for the paper: Genome-wide association study of REM sleep behavior disorder identifies novel loci with distinct polygenic and brain expression effects

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