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Qxpak.5: old mixed model solutions for new genomics problems.


ABSTRACT:

Background

Mixed models have a long and fruitful history in statistics. They are pertinent to genomics problems because they are highly versatile, accommodating a wide variety of situations within the same theoretical and algorithmic framework.

Results

Qxpak is a package for versatile statistical genomics, specifically designed for sophisticated quantitative trait loci and association analyses. Multiple loci, multiple trait, infinitesimal genetic effects, imprinting, epistasis or sex linked loci can be fitted. The new version (v. 5) allows us, among other new features, to include either relationship matrices obtained with molecular information or user defined matrices that can be read from an input file. This feature can be used for genome selection or - more importantly - to correct for population structure in association studies. In crosses, two parental lines, not necessarily inbred, can be accommodated.

Conclusions

This software aims at simplifying statistical genetic analyses implementing a coherent and unified approach by mixed models. It provides a tool that can be used in a wide variety of situations with ample genetic and statistical modeling flexibility. The software, a complete manual and examples are available at http://www.icrea.cat/Web/OtherSectionViewer.aspx?key=485&titol=Software:Qxpak.

SUBMITTER: Perez-Enciso M 

PROVIDER: S-EPMC3123239 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Qxpak.5: old mixed model solutions for new genomics problems.

Pérez-Enciso Miguel M   Misztal Ignacy I  

BMC bioinformatics 20110525


<h4>Background</h4>Mixed models have a long and fruitful history in statistics. They are pertinent to genomics problems because they are highly versatile, accommodating a wide variety of situations within the same theoretical and algorithmic framework.<h4>Results</h4>Qxpak is a package for versatile statistical genomics, specifically designed for sophisticated quantitative trait loci and association analyses. Multiple loci, multiple trait, infinitesimal genetic effects, imprinting, epistasis or  ...[more]

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