Glow
v1.1.1
Introduction to Glow
Getting Started
Variant Data Manipulation
Tertiary Analysis
Parallelizing Command-Line Bioinformatics Tools With the Pipe Transformer
Using Python Statistics Libraries
GloWGR: Whole Genome Regression
GloWGR: Genome-Wide Association Study (GWAS) Regression Tests
Troubleshooting
Blog Posts
Additional Resources
Python API
Glow
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Tertiary Analysis
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Tertiary Analysis
Perform population-scale statistical analyses of genetic variants.
Parallelizing Command-Line Bioinformatics Tools With the Pipe Transformer
Usage
Integrating with bioinformatics tools
Options
Cleanup
Using Python Statistics Libraries
pandas example notebook
GloWGR: Whole Genome Regression
Performance
Overview
Data preparation
Stage 1. Genotype matrix blocking
Stage 2. Dimensionality reduction
Stage 3. Estimate phenotypic predictors
Proceed to GWAS
Troubleshooting
GloWGR: Genome-Wide Association Study (GWAS) Regression Tests
Linear regression
Logistic regression
Offset
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v: v1.1.1
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