Relative evolutionary rate inference in HyPhy with LEISR

Stephanie J. Spielman, Sergei L.Kosakovsky Pond

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We introduce LEISR (Likehood Estimation of Individual Site Rates, pronounced "laser"), a tool to infer relative evolutionary rates from protein and nucleotide data, implemented in HyPhy. LEISR is based on the popular Rate4Site (Pupko et al., 2002) approach for inferring relative site-wise evolutionary rates, primarily from protein data. We extend the original method for more general use in several key ways: (i) we increase the support for nucleotide data with additional models, (ii) we allow for datasets of arbitrary size, (iii) we support analysis of site-partitioned datasets to correct for the presence of recombination breakpoints, (iv) we produce rate estimates at all sites rather than at just a subset of sites, and (v) we implemented LEISR as MPI-enabled to support rapid, high-throughput analysis. LEISR is available in HyPhy starting with version 2.3.8, and it is accessible as an option in the HyPhy analysis menu ("Relative evolutionary rate inference"), which calls the HyPhy batchfile LEISR.bf.

Original languageEnglish (US)
Article numbere4339
JournalPeerJ
Volume2018
Issue number2
DOIs
StatePublished - 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Neuroscience(all)

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