Code necessary to conduct all data prep and analysis in the EPoCH study.
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Updated
Aug 21, 2024 - HTML
Code necessary to conduct all data prep and analysis in the EPoCH study.
🧬High-performance genetics- and genomics-related data visualization using Makie.jl
Application of the Simple Sum method for testing co-localization of GWAS with any other SNP-level data (e.g. eQTL data)
Scalable Implementation of generalized mixed models using GDS files in Phenome-Wide Association Studies
Tools for preprocessing, QC, and preliminary analyses from raw UK BioBank data
Those are the code files for producing the PheWAS analyses in the manuscript "Phenome-Wide Association Study of Polygenic Risk Score for Alzheimer’s Disease in Electronic Health Records". Part of our analyses included sensitive genomic data. Codes to produce AD PRS were not included here.
Python package for efficient genetic association analyses
metaUSAT is a data-adaptive statistical approach for testing genetic associations of multiple traits from single/multiple studies using univariate GWAS summary statistics.
hGMNet : host Genetics and Microbe interaction Networks
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