LFMM: Latent Factor Mixed Models

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

Main authors: Eric Frichot, Kevin Caye, Olivier Francois

R package: lfmm (updated December, 2017)

New latent factor algorithms are available in functions of the R package lfmm (recommended for large data sets). For documentation and examples, see lfmm (github devel version).

R version: 1.5 (updated May, 2017)

The LFMM software is available in a function of the R package LEA (recommended use). The R package contains documentation files and examples. See the LEA website.

Version: 1.5 (updated May, 2017)

The LFMM software is available in a command line version (CL) for Linux and Mac Operating System, and with a Graphical User Interface (GUI) for Windows, Linux and Mac Operating System (OS). The package contains documentation files, perl and R scripts and a tutorial example. LFMM does not accept missing genotypes. Use a genotype imputation method before fitting models. See the R function LEA::impute() for an imputation method.

We recommend using the R package LEA 2.0.0 (version (CL_v1.5)) or the R package lfmm (devel version).

Graphical User Interface version (GUI) (v 1.2):