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CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis
Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of comp...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3808451/ https://www.ncbi.nlm.nih.gov/pubmed/24204223 http://dx.doi.org/10.1371/journal.pcbi.1003270 |
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author | Tyler, Anna L. Lu, Wei Hendrick, Justin J. Philip, Vivek M. Carter, Gregory W. |
author_facet | Tyler, Anna L. Lu, Wei Hendrick, Justin J. Philip, Vivek M. Carter, Gregory W. |
author_sort | Tyler, Anna L. |
collection | PubMed |
description | Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape. |
format | Online Article Text |
id | pubmed-3808451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38084512013-11-07 CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis Tyler, Anna L. Lu, Wei Hendrick, Justin J. Philip, Vivek M. Carter, Gregory W. PLoS Comput Biol Research Article Contemporary genetic studies are revealing the genetic complexity of many traits in humans and model organisms. Two hallmarks of this complexity are epistasis, meaning gene-gene interaction, and pleiotropy, in which one gene affects multiple phenotypes. Understanding the genetic architecture of complex traits requires addressing these phenomena, but interpreting the biological significance of epistasis and pleiotropy is often difficult. While epistasis reveals dependencies between genetic variants, it is often unclear how the activity of one variant is specifically modifying the other. Epistasis found in one phenotypic context may disappear in another context, rendering the genetic interaction ambiguous. Pleiotropy can suggest either redundant phenotype measures or gene variants that affect multiple biological processes. Here we present an R package, R/cape, which addresses these interpretation ambiguities by implementing a novel method to generate predictive and interpretable genetic networks that influence quantitative phenotypes. R/cape integrates information from multiple related phenotypes to constrain models of epistasis, thereby enhancing the detection of interactions that simultaneously describe all phenotypes. The networks inferred by R/cape are readily interpretable in terms of directed influences that indicate suppressive and enhancing effects of individual genetic variants on other variants, which in turn account for the variance in quantitative traits. We demonstrate the utility of R/cape by analyzing a mouse backcross, thereby discovering novel epistatic interactions influencing phenotypes related to obesity and diabetes. R/cape is an easy-to-use, platform-independent R package and can be applied to data from both genetic screens and a variety of segregating populations including backcrosses, intercrosses, and natural populations. The package is freely available under the GPL-3 license at http://cran.r-project.org/web/packages/cape. Public Library of Science 2013-10-24 /pmc/articles/PMC3808451/ /pubmed/24204223 http://dx.doi.org/10.1371/journal.pcbi.1003270 Text en © 2013 Tyler 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Tyler, Anna L. Lu, Wei Hendrick, Justin J. Philip, Vivek M. Carter, Gregory W. CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title | CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title_full | CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title_fullStr | CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title_full_unstemmed | CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title_short | CAPE: An R Package for Combined Analysis of Pleiotropy and Epistasis |
title_sort | cape: an r package for combined analysis of pleiotropy and epistasis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3808451/ https://www.ncbi.nlm.nih.gov/pubmed/24204223 http://dx.doi.org/10.1371/journal.pcbi.1003270 |
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