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.

The method estimates a linear combination of environmental variables, called an environmental score (ES), that interacts with genetic markers throughout the genome, and provides a readily interpretable way to examine the combined effect of many environmental variables. The ES can be used both to estimate the proportion of phenotypic variance attributable to GxE effects, and also to test for GxE effects at genetic variants across the genome.



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

Matthew Kerin and Jonathan Marchini (2020) Gene-environment interactions using a Bayesian whole genome regression model [bioRxiv][Journal]


27 April 2020 (v1.0) : First public release

Software registration and license:

LEMMA has a documentation webpage and source code on Github. LEMMA is freely available under an MIT licence.


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