Abstract
Genes undergo distinct selective sweeps, and also interact and coevolve, forming the bases of complex phenotypic traits. Therefore, the identification of genes that coevolve or are under artificial selective sweeps is of great importance. However, previous computational methods have been designed for either populations of closely related breeds or individuals of distinct species. Approaches intended specifically for closely related individuals without replicate (i.e. each breed/strain is represented by only one individual) are long overdue. We present a free, powerful, open source package, pyRSD-CoEv, that allows the identification of genes undergoing coevolution and/or selection-based sweeps. pyRSD-CoEv includes two main analysis workflows for genomic variant data: (i) the identification of selective sweeps using relative homozygous single nucleotide variant density (RSD); and (ii) the identification of coevolutionary gene clusters based on correlated evolutionary rates. The python package pyRSD-CoEv is written using python 3.7 and is freely available from the github website at https://github.com/QianZiTang/pyRSD-CoEv. It runs on Linux.
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