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QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern
BACKGROUND: Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have develo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160955/ https://www.ncbi.nlm.nih.gov/pubmed/21794153 http://dx.doi.org/10.1186/1471-2156-12-66 |
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author | Cheng, Riyan Abney, Mark Palmer, Abraham A Skol, Andrew D |
author_facet | Cheng, Riyan Abney, Mark Palmer, Abraham A Skol, Andrew D |
author_sort | Cheng, Riyan |
collection | PubMed |
description | BACKGROUND: Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. RESULTS: We have successfully used the package to analyze many datasets, including F(34 )body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. CONCLUSIONS: QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis. |
format | Online Article Text |
id | pubmed-3160955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31609552011-08-25 QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern Cheng, Riyan Abney, Mark Palmer, Abraham A Skol, Andrew D BMC Genet Software BACKGROUND: Existing software for quantitative trait mapping is either not able to model polygenic variation or does not allow incorporation of more than one genetic variance component. Improperly modeling the genetic relatedness among subjects can result in excessive false positives. We have developed an R package, QTLRel, to enable more flexible modeling of genetic relatedness as well as covariates and non-genetic variance components. RESULTS: We have successfully used the package to analyze many datasets, including F(34 )body weight data that contains 688 individuals genotyped at 3105 SNP markers and identified 11 QTL. It took 295 seconds to estimate variance components and 70 seconds to perform the genome scan on an Linux machine equipped with a 2.40GHz Intel(R) Core(TM)2 Quad CPU. CONCLUSIONS: QTLRel provides a toolkit for genome-wide association studies that is capable of calculating genetic incidence matrices from pedigrees, estimating variance components, performing genome scans, incorporating interactive covariates and genetic and non-genetic variance components, as well as other functionalities such as multiple-QTL mapping and genome-wide epistasis. BioMed Central 2011-07-27 /pmc/articles/PMC3160955/ /pubmed/21794153 http://dx.doi.org/10.1186/1471-2156-12-66 Text en Copyright ©2011 Cheng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Cheng, Riyan Abney, Mark Palmer, Abraham A Skol, Andrew D QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title | QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title_full | QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title_fullStr | QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title_full_unstemmed | QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title_short | QTLRel: an R Package for Genome-wide Association Studies in which Relatedness is a Concern |
title_sort | qtlrel: an r package for genome-wide association studies in which relatedness is a concern |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160955/ https://www.ncbi.nlm.nih.gov/pubmed/21794153 http://dx.doi.org/10.1186/1471-2156-12-66 |
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