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simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes
BACKGROUND: Advances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy)....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7603745/ https://www.ncbi.nlm.nih.gov/pubmed/33129253 http://dx.doi.org/10.1186/s12859-020-03804-y |
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author | Fernandes, Samuel B. Lipka, Alexander E. |
author_facet | Fernandes, Samuel B. Lipka, Alexander E. |
author_sort | Fernandes, Samuel B. |
collection | PubMed |
description | BACKGROUND: Advances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy). As the demand for multivariate analyses increases, it is imperative that optimal tools are available to assess their performance. To facilitate the testing and validation of these multivariate approaches, we developed simplePHENOTYPES, an R/CRAN package that simulates pleiotropy, partial pleiotropy, and spurious pleiotropy in a wide range of genetic architectures, including additive, dominance and epistatic models. RESULTS: We illustrate simplePHENOTYPES’ ability to simulate thousands of phenotypes in less than one minute. We then provide two vignettes illustrating how to simulate sets of correlated traits in simplePHENOTYPES. Finally, we demonstrate the use of results from simplePHENOTYPES in a standard GWAS software, as well as the equivalence of simulated phenotypes from simplePHENOTYPES and other packages with similar capabilities. CONCLUSIONS: simplePHENOTYPES is a R/CRAN package that makes it possible to simulate multiple traits controlled by loci with varying degrees of pleiotropy. Its ability to interface with both commonly-used marker data formats and downstream quantitative genetics software and packages should facilitate a rigorous assessment of both existing and emerging statistical GWAS and GS approaches. simplePHENOTYPES is also available at https://github.com/samuelbfernandes/simplePHENOTYPES. |
format | Online Article Text |
id | pubmed-7603745 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76037452020-11-02 simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes Fernandes, Samuel B. Lipka, Alexander E. BMC Bioinformatics Software BACKGROUND: Advances in genotyping and phenotyping techniques have enabled the acquisition of a great amount of data. Consequently, there is an interest in multivariate statistical analyses that identify genomic regions likely to contain causal mutations affecting multiple traits (i.e., pleiotropy). As the demand for multivariate analyses increases, it is imperative that optimal tools are available to assess their performance. To facilitate the testing and validation of these multivariate approaches, we developed simplePHENOTYPES, an R/CRAN package that simulates pleiotropy, partial pleiotropy, and spurious pleiotropy in a wide range of genetic architectures, including additive, dominance and epistatic models. RESULTS: We illustrate simplePHENOTYPES’ ability to simulate thousands of phenotypes in less than one minute. We then provide two vignettes illustrating how to simulate sets of correlated traits in simplePHENOTYPES. Finally, we demonstrate the use of results from simplePHENOTYPES in a standard GWAS software, as well as the equivalence of simulated phenotypes from simplePHENOTYPES and other packages with similar capabilities. CONCLUSIONS: simplePHENOTYPES is a R/CRAN package that makes it possible to simulate multiple traits controlled by loci with varying degrees of pleiotropy. Its ability to interface with both commonly-used marker data formats and downstream quantitative genetics software and packages should facilitate a rigorous assessment of both existing and emerging statistical GWAS and GS approaches. simplePHENOTYPES is also available at https://github.com/samuelbfernandes/simplePHENOTYPES. BioMed Central 2020-10-31 /pmc/articles/PMC7603745/ /pubmed/33129253 http://dx.doi.org/10.1186/s12859-020-03804-y Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Fernandes, Samuel B. Lipka, Alexander E. simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title | simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title_full | simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title_fullStr | simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title_full_unstemmed | simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title_short | simplePHENOTYPES: SIMulation of pleiotropic, linked and epistatic phenotypes |
title_sort | simplephenotypes: simulation of pleiotropic, linked and epistatic phenotypes |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7603745/ https://www.ncbi.nlm.nih.gov/pubmed/33129253 http://dx.doi.org/10.1186/s12859-020-03804-y |
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