BOLT-LMM 2.3.2-foss-2018b
Deprecated: Use of this version of BOLT-LMM is deprecated. More information on our Applications Support and Retention Policy.
The 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, BEAR Cloud VMs, and CaStLeS VMs):
module load BOLT-LMM/2.3.2-foss-2018b
BEAR Apps Version
Architectures
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
- BEAR Cloud and CaStLeS VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
More Information
For more information visit the BOLT-LMM website.
Dependencies
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