If you use this software in your research, please cite the references listed below.
The Sparse Marginal Epistasis Test (SME)
Stamp J, Smith Pattillo S, Weinreich D, Crawford L (2025). Sparse modeling of interactions enables fast detection of genome-wide epistasis in biobank-scale studies. biorxiv, https://doi.org/10.1101/2025.01.11.632557
Stamp J & Crawford L (2025). smer: Sparse Marginal Epistasis Test. https://github.com/lcrawlab/sme, https://lcrawlab.github.io/sme/
The multivariate Marginal Epistasis Test (mvMAPIT)
Stamp J, DenAdel A, Weinreich D, Crawford, L (2023). Leveraging the Genetic Correlation between Traits Improves the Detection of Epistasis in Genome-wide Association Studies. G3 Genes|Genomes|Genetics 13(8), jkad118; doi: https://doi.org/10.1093/g3journal/jkad118
Stamp J, Crawford L (2022). mvMAPIT: Multivariate Genome Wide Marginal Epistasis Test. https://github.com/lcrawlab/mvMAPIT, https://lcrawlab.github.io/mvMAPIT/
The Marginal Epistasis Test (MAPIT)
Crawford L, Zeng P, Mukherjee S, & Zhou X (2017). Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits. PLoS genetics, 13(7), e1006869. https://doi.org/10.1371/journal.pgen.1006869