LFMM: Latent Factor Mixed Models

A unified framework for inferring latent confounders and gene-environment (and other) associations

December 2017: A new release of the LFMM program is available from github in the R package lfmm. The new implementation of LFMM is based on least squares estimates. The "lfmm" functions are faster for larger data sets and they are sometimes more accurate than the Bayesian version.

October 2017: Major update of the R package LEA including imputation functions. The Bayesian program LFMM 1.5 is still available in LEA.

Publications referencing LFMM:

E. Frichot, S.D. Schoville, G. Bouchard, O. François (2013) Testing for associations between loci and environmental gradients using latent factor mixed models Molecular Biology and Evolution, 30 (7), 1687-1699. Link to MBE.

E Frichot, O Francois (2015) LEA: An R Package for Landscape and Ecological Association Studies, Methods in Ecology and Evolution6 (8), 925–929.