Implementation of MAGEE workflow for efficient, large-scale aggregate and single-variant tests of gene-environment interaction in related individuals.
This workflow implements the MAGEE (Mixed Model Association Test for GEne-Environment Interaction) tool (https://github.com/large-scale-gxe-methods/MAGEE). MAGEE conducts genome-wide gene-environment interaction tests of single variants and aggregate tests of variant groups, while allowing for related individuals and inclusion of multiple exposures.
Author: Kenny Westerman (kewesterman@mgh.harvard.edu)
MAGEE tool information:
- Manuscript: X Wang et al. Efficient gene–environment interaction tests for large biobank-scale sequencing studies. Genetic Epidemiology. 2020; 44(8): 908-923. https://doi.org/10.1002/gepi.22351.
- Source code: https://github.com/large-scale-gxe-methods/MAGEE
Workflow steps:
- Run null model
- Run MAGEE (single-variant or aggregate; scattered across an array of input files, usually chromosomes)
- Concatenate the outputs into a single summary statistics file
Inputs:
See the "parameter_meta" section of the .wdl script.
Outputs:
- A summary statistics file containing estimates for genetic main effects and interaction effects as well as p-values for these along with a joint test of genetic main and interaction effects.
- A file containing additional score statistics and covariances necessary for meta-analysis.