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.
Bioinformatics. 2019 Nov 1;35(22):4815-4817. doi: 10.1093/bioinformatics/btz468.
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.
当生物体的不同谱系独立适应相似的环境时,选择通常会反复作用于相同的基因,导致这些基因的趋同进化率变化特征。随着越来越多具有各种趋同特征的生物体的基因组序列可用,识别具有这种趋同速率特征的基因的能力将使我们能够深入了解这些特征的分子基础。
在这里,我们介绍了 R 包 RERconverge,它测试了基因的相对进化率与整个系统发育中特征进化之间的关联。RERconverge 可以与二元和连续特征进行关联,并且它包含用于关联结果可视化和富集分析的工具。
RERconverge 的源代码、文档和详细使用说明可在 https://github.com/nclark-lab/RERconverge 上免费获得。哺乳动物、果蝇和酵母的数据集可在 https://bit.ly/2J2QBnj 获得。
补充数据可在《生物信息学》在线获得。