<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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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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