2012年6月17日 · Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods in terms...

This directory contains the mlmm package for the R programming language. It implements an efficient multi-locus mixed-model approach for genome-wide association studies in structured populations.

First, MLMM is a simple, stepwise mixed-model regression with forward inclusion and backward elimination and FASTmrEMMA is a two-step combined method. In MLMM, the computationally intensive forward-backward inclusion of SNPs is clearly a limiting factor in exploring the huge model space [ 17 ].

MLMM - An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations

2016年2月1日 · The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship.

Two main functions can be used to carry out GWAS with MLMM and plot the results from the analysis: mlmm, the original MLMM as described in Segura, Vilhjálmsson et al. (Nat Gen 2012). mlmm_cof, a modified version of MLMM that allows including a fixed covariate in …

2020年8月1日 · There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs.