BOLT-LMM 2.3.2-foss-2018bThe BOLT-LMM software package currently consists of two main algorithms, the BOLT-LMM algorithm for mixed model association testing, and the BOLT-REML algorithm for variance components analysis (i.e., partitioning of SNP-heritability and estimation of genetic correlations). We recommend BOLT-LMM for analyses of human genetic data sets containing more than 5,000 samples. The algorithms used in BOLT-LMM rely on approximations that hold only at large sample sizes and have been tested only in human data sets. For analyses of fewer than 5,000 samples, we recommend the GCTA or GEMMA software. We also note that BOLT-LMM association test statistics are valid for quantitative traits and for (reasonably) balanced case-control traits. For unbalanced case-control traits, we recommend the recent SAIGE software.
Accessing BOLT-LMM 2.3.2-foss-2018b
To load the module for BOLT-LMM 2.3.2-foss-2018b please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load BOLT-LMM/2.3.2-foss-2018b
BEAR Apps Version
For more information visit the BOLT-LMM website.
This version of BOLT-LMM has a direct dependency on: Boost/1.67.0-foss-2018b foss/2018b NLopt/2.4.2-GCCcore-7.3.0
Last modified on 3rd June 2019