Inference of Episodic Changes in Natural Selection Acting on Protein Coding Sequences via CODEML. Issue 1 (20th June 2016)

• Record Type: Journal Article
• Authors: Bielawski, Joseph P.; Baker, Jennifer L.; Mingrone, Joseph
• Editors: Bateman, Alex; Pearson, William R.; Stein, Lincoln D.; Stormo, Gary D.; Yates, John R.
• Is Part Of: Current protocols in bioinformatics. Volume 54:Issue 1(2016)
• Page Start: 6.15.1
• Page End: 6.15.32
• Publication Date: 2016-06-20
• Subjects: codon model -- natural selection -- episodic evolution -- maximum likelihood -- dN/dS ratio -- experimental design; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.2
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: 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.