Inference of Episodic Changes in Natural Selection Acting on Protein Coding Sequences via CODEML.
This unit provides protocols for using the CODEML program from the PAML package to make inferences about episodic natural selection in protein-coding sequences. The protocols cover inference tasks such as maximum likelihood estimation of selection intensity, testing the hypothesis of episodic positive selection, and identifying sites with a history of episodic evolution. We provide protocols for using the rich set of models implemented in CODEML to assess robustness, and for using bootstrapping to assess if the requirements for reliable statistical inference have been met. An example dataset is used to illustrate how the protocols are used with real protein-coding sequences. The workflow of this design, through automation, is readily extendable to a larger-scale evolutionary survey. © 2016 by John Wiley & Sons, Inc.
Department of Biology, Dalhousie University, Halifax, Nova Scotia, Canada.|Department of Mathematics & Statistics, Dalhousie University, Halifax, Nova Scotia, Canada.
Joseph P
JP
Bielawski
Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland.
Jennifer L
JL
Baker
Department of Mathematics & Statistics, Dalhousie University, Halifax, Nova Scotia, Canada.
Joseph
J
Mingrone
D003062:Codon / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D016013:Likelihood Functions; D012641:Selection, Genetic; D012984:Software
D003062:Codon
codon model; dN/dS ratio; episodic evolution; experimental design; maximum likelihood; natural selection