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Overview

This repository provides software for the following two methods:

  • LEMMA (Linear Environment Mixed Model Analysis) is a whole genome wide regression method for flexible modeling of gene-environment interactions in large datasets such as the UK Biobank.
  • GPLEMMA (Gaussian Prior Linear Environment Mixed Model Analysis) non-linear randomized Haseman-Elston regression method for flexible modeling of gene-environment interactions in large datasets such as the UK Biobank.

For documentation please see the following webpage: https://mkerin.github.io/LEMMA/

Citation

If you use LEMMA in your research, please cite the following publication:

Matthew Kerin and Jonathan Marchini (2020) Inferring Gene-by-Environment Interactions with a Bayesian Whole-Genome Regression Model [AJHG]

If you use GPLEMMA in your research, please cite the following publication:

Matthew Kerin and Jonathan Marchini (2020) Non-linear randomized Haseman-Elston regression for estimation of gene-environment heritability [Bioinformatics][bioRxiv]