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Limited utility of residue masking for positive-selection inference.
Spielman, Stephanie J; Dawson, Eric T; Wilke, Claus O.
Affiliation
  • Spielman SJ; Department of Integrative Biology, Center for Computational Biology and Bioinformatics, and Institute of Cellular and Molecular Biology, The University of Texas at Austin stephanie.spielman@gmail.com.
  • Dawson ET; Department of Integrative Biology, Center for Computational Biology and Bioinformatics, and Institute of Cellular and Molecular Biology, The University of Texas at Austin.
  • Wilke CO; Department of Integrative Biology, Center for Computational Biology and Bioinformatics, and Institute of Cellular and Molecular Biology, The University of Texas at Austin.
Mol Biol Evol ; 31(9): 2496-500, 2014 Sep.
Article in En | MEDLINE | ID: mdl-24899665
ABSTRACT
Errors in multiple sequence alignments (MSAs) can reduce accuracy in positive-selection inference. Therefore, it has been suggested to filter MSAs before conducting further analyses. One widely used filter, Guidance, allows users to remove MSA positions aligned with low confidence. However, Guidance's utility in positive-selection inference has been disputed in the literature. We have conducted an extensive simulation-based study to characterize fully how Guidance impacts positive-selection inference, specifically for protein-coding sequences of realistic divergence levels. We also investigated whether novel scoring algorithms, which phylogenetically corrected confidence scores, and a new gap-penalization score-normalization scheme improved Guidance's performance. We found that no filter, including original Guidance, consistently benefitted positive-selection inferences. Moreover, all improvements detected were exceedingly minimal, and in certain circumstances, Guidance-based filters worsened inferences.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Alignment / Computational Biology Type of study: Prognostic_studies Language: En Journal: Mol Biol Evol Journal subject: BIOLOGIA MOLECULAR Year: 2014 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sequence Alignment / Computational Biology Type of study: Prognostic_studies Language: En Journal: Mol Biol Evol Journal subject: BIOLOGIA MOLECULAR Year: 2014 Document type: Article