deb_control_files:
- control
- md5sums
deb_fields:
Architecture: amd64
Depends: libc6 (>= 2.38), libgcc-s1 (>= 3.0), libgsl28 (>= 2.8+dfsg), libopenblas0,
libstdc++6 (>= 13.1), zlib1g (>= 1:1.1.4)
Description: |-
Genome-wide Efficient Mixed Model Association
GEMMA is the software implementing the Genome-wide Efficient Mixed
Model Association algorithm for a standard linear mixed model and some
of its close relatives for genome-wide association studies (GWAS):
.
* It fits a univariate linear mixed model (LMM) for marker association
tests with a single phenotype to account for population stratification
and sample structure, and for estimating the proportion of variance in
phenotypes explained (PVE) by typed genotypes (i.e. "chip heritability").
* It fits a multivariate linear mixed model (mvLMM) for testing marker
associations with multiple phenotypes simultaneously while controlling
for population stratification, and for estimating genetic correlations
among complex phenotypes.
* It fits a Bayesian sparse linear mixed model (BSLMM) using Markov
chain Monte Carlo (MCMC) for estimating PVE by typed genotypes,
predicting phenotypes, and identifying associated markers by jointly
modeling all markers while controlling for population structure.
* It estimates variance component/chip heritability, and partitions
it by different SNP functional categories. In particular, it uses HE
regression or REML AI algorithm to estimate variance components when
individual-level data are available. It uses MQS to estimate variance
components when only summary statisics are available.
.
GEMMA is computationally efficient for large scale GWAS and uses freely
available open-source numerical libraries.
Homepage: https://www.xzlab.org/software.html
Installed-Size: '1289'
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Package: gemma
Priority: optional
Section: science
Version: 0.98.5+dfsg-3
srcpkg_name: gemma
srcpkg_version: 0.98.5+dfsg-3