GWAS Tutorial

This is a quickstart tutorial for performing genome-wide association studies using Glow.

You can view html versions of the notebooks and download them from the bottom of this page.

The notebooks are written in Python, with some visualization in R.


We recommend running the Data Simulation notebooks first to prepare data for this tutorial before trying with your own data.


Notebooks in the Glow documentation are tested nightly.

1. Quality Control

The first notebook in this series prepares data by performing standard quality control procedures on simulated genotype data.

2. Glow Whole Genome Regression (GloWGR)

GloWGR implements a distributed version of the Regenie method. Please review the Regenie paper in Nature Genetics and the Regenie Github repo before implementing this method on real data.

3. Regression

The GloWGR notebook calculated offsets that are used in the genetic association study below to control for population structure and relatedness.

Quantitative glow whole genome regression

Binary glow whole genome regression