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

Author:

Kowalczyk Amanda12,Meyer Wynn K1ORCID,Partha Raghavendran12,Mao Weiguang12,Clark Nathan L12,Chikina Maria12

Affiliation:

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

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

Abstract

Abstract Motivation 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. Results 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. Availability and implementation 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 information Supplementary data are available at Bioinformatics online.

Funder

National Institutes of Health

University of Pittsburgh Center for Research Computing

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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