RERconverge: an R package for associating evolutionary rates with convergent traits.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 11 2019
Historique:
received: 30 11 2018
revised: 08 04 2019
accepted: 06 06 2019
pubmed: 14 6 2019
medline: 25 6 2020
entrez: 14 6 2019
Statut: ppublish

Résumé

When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits. Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results. RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 31192356
pii: 5514536
doi: 10.1093/bioinformatics/btz468
pmc: PMC6853647
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4815-4817

Subventions

Organisme : NHGRI NIH HHS
ID : R01 HG009299
Pays : United States
Organisme : NIBIB NIH HHS
ID : T32 EB009403
Pays : United States

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Auteurs

Amanda Kowalczyk (A)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.

Wynn K Meyer (WK)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.

Raghavendran Partha (R)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.

Weiguang Mao (W)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.

Nathan L Clark (NL)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.

Maria Chikina (M)

Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Joint Carnegie Mellon University-University of Pittsburgh Ph.D. Program in Computational Biology, Pittsburgh, PA 15213, USA.

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