CodABC: A computational framework to coestimate recombination, substitution, and molecular adaptation rates by approximate bayesian computation

Miguel Arenas*, Joao S. Lopes, Mark A. Beaumont, David Posada

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
236 Downloads (Pure)

Abstract

The estimation of substitution and recombination rates can provide important insights into the molecular evolution of protein-coding sequences. Here, we present a new computational framework, called "CodABC," to jointly estimate recombination, substitution and synonymous and nonsynonymous rates from coding data. CodABC uses approximate Bayesian computation with and without regression adjustment and implements a variety of codon models, intracodon recombination, and longitudinal sampling. CodABC can provide accurate joint parameter estimates from recombining coding sequences, often outperforming maximum-likelihood methods based on more approximate models. In addition, CodABC allows for the inclusion of several nuisance parameters such as those representing codon frequencies, transition matrices, heterogeneity across sites or invariable sites. CodABC is freely available from http://code.google.com/p/codabc/, includes a GUI, extensive documentation and ready-to-use examples, and can run in parallel on multicore machines.

Original languageEnglish
Pages (from-to)1109-1112
Number of pages4
JournalMolecular Biology and Evolution
Volume32
Issue number4
Early online date9 Jan 2015
DOIs
Publication statusPublished - 1 Apr 2015

Keywords

  • approximate Bayesian computation
  • coding data
  • molecular adaptation
  • recombination
  • substitution rate

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