MMAP / MMAP-releases-issues-Q-and-A

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https://MMAP.github.io
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gwas mixed-model-analysis mixed-models mmap pedigree

MMAP by Jeff O'Connell

Latest Release     Issues and Q&A

MMAP: Mixed Model Analysis for Pedigrees and Populations

MMAP is a comprehensive mixed model program for analysis of pedigree and population data. It provides an optimized and flexible platform that incorporates a wide range of covariance structures such as additive, dominance, epistasis, maternal and imprinting using pedigree and/or genotype data and also allows users to define their own covariance structures. Likelihood calculations use multi-threaded optimized matrix libraries to handle multiple random effects. MMAP can import data from a variety of imputation programs to avoid data manipulation and IBS/IBD programs to build covariance structures.

MMAP uses a fast low-memory method to calculate additive and dominant genetic covariance structures using SNP data, which can be quite challenging for large data sets. For polygenic SNP analysis MMAP can store SNP-covariance products to reduce the complexity subsequent analyses with the same subjects to linear regression, independent of phenotype or covariates.

Installation

MMAP is statically compiled with the Intel Math Kernel library for the Unix/Linux environment and uses BLAS and LAPACK libraries. To ensure compatibility only a static executable is currently available. After download, be sure to make the file executable. Click here to download MMAP.

MMAP website

Visit the MMAP website for the complete guide to using MMAP.