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Funmap2: an R package for QTL mapping using longitudinal phenotypes

Quantitative trait locus (QTL) mapping has been used as a powerful tool for inferring the complexity of the genetic architecture that underlies phenotypic traits. This approach has shown its unique power to map the developmental genetic architecture of complex traits by implementing longitudinal dat...

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Detalles Bibliográficos
Autores principales: Wang, Nating, Chu, Tinyi, Luo, Jiangtao, Wu, Rongling, Wang, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546077/
https://www.ncbi.nlm.nih.gov/pubmed/31183256
http://dx.doi.org/10.7717/peerj.7008
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author Wang, Nating
Chu, Tinyi
Luo, Jiangtao
Wu, Rongling
Wang, Zhong
author_facet Wang, Nating
Chu, Tinyi
Luo, Jiangtao
Wu, Rongling
Wang, Zhong
author_sort Wang, Nating
collection PubMed
description Quantitative trait locus (QTL) mapping has been used as a powerful tool for inferring the complexity of the genetic architecture that underlies phenotypic traits. This approach has shown its unique power to map the developmental genetic architecture of complex traits by implementing longitudinal data analysis. Here, we introduce the R package Funmap2 based on the functional mapping framework, which integrates prior biological knowledge into the statistical model. Specifically, the functional mapping framework is engineered to include longitudinal curves that describe the genetic effects and the covariance matrix of the trait of interest. Funmap2 chooses the type of longitudinal curve and covariance matrix automatically using information criteria. Funmap2 is available for download at https://github.com/wzhy2000/Funmap2.
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spelling pubmed-65460772019-06-10 Funmap2: an R package for QTL mapping using longitudinal phenotypes Wang, Nating Chu, Tinyi Luo, Jiangtao Wu, Rongling Wang, Zhong PeerJ Bioinformatics Quantitative trait locus (QTL) mapping has been used as a powerful tool for inferring the complexity of the genetic architecture that underlies phenotypic traits. This approach has shown its unique power to map the developmental genetic architecture of complex traits by implementing longitudinal data analysis. Here, we introduce the R package Funmap2 based on the functional mapping framework, which integrates prior biological knowledge into the statistical model. Specifically, the functional mapping framework is engineered to include longitudinal curves that describe the genetic effects and the covariance matrix of the trait of interest. Funmap2 chooses the type of longitudinal curve and covariance matrix automatically using information criteria. Funmap2 is available for download at https://github.com/wzhy2000/Funmap2. PeerJ Inc. 2019-05-31 /pmc/articles/PMC6546077/ /pubmed/31183256 http://dx.doi.org/10.7717/peerj.7008 Text en ©2019 Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Wang, Nating
Chu, Tinyi
Luo, Jiangtao
Wu, Rongling
Wang, Zhong
Funmap2: an R package for QTL mapping using longitudinal phenotypes
title Funmap2: an R package for QTL mapping using longitudinal phenotypes
title_full Funmap2: an R package for QTL mapping using longitudinal phenotypes
title_fullStr Funmap2: an R package for QTL mapping using longitudinal phenotypes
title_full_unstemmed Funmap2: an R package for QTL mapping using longitudinal phenotypes
title_short Funmap2: an R package for QTL mapping using longitudinal phenotypes
title_sort funmap2: an r package for qtl mapping using longitudinal phenotypes
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546077/
https://www.ncbi.nlm.nih.gov/pubmed/31183256
http://dx.doi.org/10.7717/peerj.7008
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