# Pleiotropy-of-UKB-Metabolites

Data analysis and figure generation scripts for:
Courtney J. Smith*, Nasa Sinnott-Armstrong*, Anna Cichońska, Heli Julkunen, Eric Fauman, Peter Würtz, Jonathan K. Pritchard (2022). Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation. _bioRxiv_; doi: https://doi.org/10.1101/2022.04.02.486791

Data for this repository can be downloaded from:
Dryad under accession code https://doi.org/10.5061/dryad.79cnp5hxs
OR at https://drive.google.com/drive/u/2/folders/1KiHjx0uaOnc-rJM4Jph9cCherGcemuem

If anything is unclear, please contact Courtney Smith at courtrun@stanford.edu.

If you use these scripts or data, please cite the above Smith et al. 2022 (_bioRxiv_) paper and reference this Github repo:
https://github.com/courtrun/Pleiotropy-of-UKB-Metabolites

Directory overview
- GWAS sumstats processing folder has scripts for initial processing of summary statistics generated from GWAS
- Data Analysis has scripts for analyzing the processed GWAS summary statistics
- Figure Generation has scripts for producing the manuscript figures