<monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connectio...

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Main Authors: Gawenda Inka, Günther Torsten, Schmid Karl J
Format: Article
Language:English
Published: BMC 2011-06-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/12/265
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spelling doaj-e0ec1ec3056641a8a6f9ebc7c5714e2e2020-11-25T00:25:06ZengBMCBMC Bioinformatics1471-21052011-06-0112126510.1186/1471-2105-12-265<monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studiesGawenda InkaGünther TorstenSchmid Karl J<p>Abstract</p> <p>Background</p> <p>There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connection between naturally occurring genotypic and phenotypic variation. Coalescent simulations are commonly used in population genetics to simulate genotypes under different parameters and demographic models.</p> <p>Results</p> <p>Here, we present <monospace>phenosim</monospace>, a software to add a phenotype to genotypes generated in time-efficient coalescent simulations. Both qualitative and quantitative phenotypes can be generated and it is possible to partition phenotypic variation between additive effects and epistatic interactions between causal variants. The output formats of <monospace>phenosim</monospace> are directly usable as input for different GWAS tools. The applicability of <monospace>phenosim</monospace> is shown by simulating a genome-wide association study in <it>Arabidopsis thaliana</it>.</p> <p>Conclusions</p> <p>By using the coalescent approach to generate genotypes and <monospace>phenosim</monospace> to add phenotypes, the data sets can be used to assess the influence of various factors such as demography, genetic architecture or selection on the statistical power of association methods to detect causal genetic variants under a wide variety of population genetic scenarios. <monospace>phenosim</monospace> is freely available from the authors' website <url>http://evoplant.uni-hohenheim.de</url></p> http://www.biomedcentral.com/1471-2105/12/265
collection DOAJ
language English
format Article
sources DOAJ
author Gawenda Inka
Günther Torsten
Schmid Karl J
spellingShingle Gawenda Inka
Günther Torsten
Schmid Karl J
<monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
BMC Bioinformatics
author_facet Gawenda Inka
Günther Torsten
Schmid Karl J
author_sort Gawenda Inka
title <monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
title_short <monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
title_full <monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
title_fullStr <monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
title_full_unstemmed <monospace>phenosim</monospace> - A software to simulate phenotypes for testing in genome-wide association studies
title_sort <monospace>phenosim</monospace> - a software to simulate phenotypes for testing in genome-wide association studies
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2011-06-01
description <p>Abstract</p> <p>Background</p> <p>There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connection between naturally occurring genotypic and phenotypic variation. Coalescent simulations are commonly used in population genetics to simulate genotypes under different parameters and demographic models.</p> <p>Results</p> <p>Here, we present <monospace>phenosim</monospace>, a software to add a phenotype to genotypes generated in time-efficient coalescent simulations. Both qualitative and quantitative phenotypes can be generated and it is possible to partition phenotypic variation between additive effects and epistatic interactions between causal variants. The output formats of <monospace>phenosim</monospace> are directly usable as input for different GWAS tools. The applicability of <monospace>phenosim</monospace> is shown by simulating a genome-wide association study in <it>Arabidopsis thaliana</it>.</p> <p>Conclusions</p> <p>By using the coalescent approach to generate genotypes and <monospace>phenosim</monospace> to add phenotypes, the data sets can be used to assess the influence of various factors such as demography, genetic architecture or selection on the statistical power of association methods to detect causal genetic variants under a wide variety of population genetic scenarios. <monospace>phenosim</monospace> is freely available from the authors' website <url>http://evoplant.uni-hohenheim.de</url></p>
url http://www.biomedcentral.com/1471-2105/12/265
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AT gunthertorsten monospacephenosimmonospaceasoftwaretosimulatephenotypesfortestingingenomewideassociationstudies
AT schmidkarlj monospacephenosimmonospaceasoftwaretosimulatephenotypesfortestingingenomewideassociationstudies
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