phewas

🧬High-performance genetics- and genomics-related data visualization using Makie.jl

metaUSAT is a data-adaptive statistical approach for testing genetic associations of multiple traits from single/multiple studies using univariate GWAS summary statistics.

STAAR Pipeline for Analyzing Whole-Genome/Whole-Exome Sequencing Data in PheWAS (PheWAS Version of STAARpipeline)

Application of the Simple Sum method for testing co-localization of GWAS with any other SNP-level data (e.g. eQTL data)

Analyze human genetic knockouts to predict drug efficacy and side effects

Scalable Implementation of generalized mixed models using GDS files in Phenome-Wide Association Studies

Python package for efficient genetic association analyses

hGMNet : host Genetics and Microbe interaction Networks

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.

pyLocusZoom -- publication-ready GWAS visualization in Python: LocusZoom-style regional association plots with LD coloring, gene tracks and recombination overlays, plus Manhattan, QQ, Miami, eQTL, fine-mapping, PheWAS and forest plots. Dog and cat genomes built in.

Code necessary to conduct all data prep and analysis in the EPoCH study.

Phenome-wide association study of the major histocompatibility complex region in the Korean population identifies novel association signals

A visualisation platform for analysing disease-allele associations using HLA-PheWAS data

Joint impact of environmental and genetic determinants on the aetiology of stress-related psychiatric disorders.

STAAR Pipeline for Analyzing Whole-Genome/Whole-Exome Sequencing Data in PheWAS (PheWAS Version of STAARpipeline)

Analysis code for SNV-MWAS project

💆🏻J’ai déjà toi