An R package for creating Q-Q and manhattan plots from GWAS results

the hierfstat package

Code and simulations using biologically annotated neural networks

From QC to summary statistics

BioMM: Biological-informed Multi-stage Machine learning framework for phenotype prediction using omics data

A Python/R package for fitting linear mixed models for genome-wide association studies among related individuals

Comparison between VCF and plain text storage formats for GWAS summary statistics

CHARGE Consortium: collaboration for mapping targets from 1000G GWAS on coronary artery calcification (CAC) with Maryam Kavousi, Maxime Bos, Clint L. Miller, and Pat Peyser.

R package 📦 with ggplot2 extensions for GWAS summary statistics (still in 🚧)

Caprion pilot study

Publicly shared SNP-to-gene mappings of GWAS generated by MAGMA.

Web interface for gwas2vcf

Full analysis code and interactive Manhattan plots for "Gene-vegetarianism interactions in calcium, estimated glomerular filtration rate, and testosterone identified in genome-wide analysis across 30 biomarkers"

Genome-Wide Association Study (GWAS) and Polygenic Risk Score (PRS) Shiny App!

GWAS on rice RNA seq data, features use of statgenGWAS, and experimentation with different methods of pop. structure control

Evaluating the breeding potential of cultivated lentils for protein and amino acid content and quality

Reviewing the (preliminary) summary statistics from the COVID19 Host Genetics Initiative meta-analysis of genome-wide association studies (GWAS).

weighted GWAS (heteroskedastic GWAS)

This method incorporates dense linkage disequilibrium block structure of SNPs for prioritizing a set of genetic variants using GWAS summary statisticis before performing fine-mapping.