🧬High-performance genetics- and genomics-related data visualization using Makie.jl
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Updated
Jun 15, 2024 - Julia
🧬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.
Tools for preprocessing, QC, and preliminary analyses from raw UK BioBank data
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
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.
Code necessary to conduct all data prep and analysis in the EPoCH study.
Joint impact of environmental and genetic determinants on the aetiology of stress-related psychiatric disorders.
A visualisation platform for analysing disease-allele associations using HLA-PheWAS data
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