MBE Advance Access published online on March 5, 2007
Molecular Biology and Evolution, doi:10.1093/molbev/msm042
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RESEARCH ARTICLE |
Multiple Hypothesis Testing to Detect Lineages Under Positive Selection that Affects Only a Few Sites
Department of Biology, and Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), University College London, London, UK
* Address for correspondence: Ziheng Yang, Department of Biologys, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK. Tel: +44 (20) 7679 4379, Fax: +44 (20) 7679 7096. Email: z.yang{at}ucl.ac.uk
Received for publication January 26, 2007. Accepted for publication February 26, 2007.
Detection of positive Darwinian selection has become ever more important with the rapid growth of genomic data sets. Recent branch-site models of codon substitution account for variation of selective pressure over branches on the tree and across sites in the sequence, and provide a means to detect short episodes of molecular adaptation affecting just a few sites. In likelihood ratio tests based on such models, the branches to be tested for positive selection have to be specified a priori. In the absence of a biological hypothesis to designate so-called foreground branches, one may test many branches, but a correction for multiple testing becomes necessary. In this paper, we employ computer simulation to evaluate the performance of six multiple-test correction procedures when the branch-site models are used to test every branch on the phylogeny for positive selection. Four of the methods control the family-wise error rates (FWER) while the other two control the false discovery rate (FDR). We found that all correction procedures achieved acceptable FWER except for extremely divergent sequences and serious model violations, when the test may become unreliable. The power of the test to detect positive selection is influenced by the strength of selection and the sequence divergence, with the highest power observed at intermediate divergences. The four correction procedures that control the FWER had similar power. We recommend Rom's procedure for its slightly higher power, but the simple Bonferroni correction is useable as well. The two correction procedures that control the FDR had slightly more power but also higher FWER. We demonstrate the multiple-test procedures by analyzing gene sequences from the extracellular domain of the cluster of differentiation 2 gene (CD2) from 10 mammalian species. Both our simulation and real data analysis suggest that the multiple-test procedures are useful when multiple branches have to be tested on the same data set.
Key Words: Multiple hypothesis testing • family-wise error rate (FWER) • false discovery rate (FDR) • positive selection • branch-site model • molecular adaptation
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