Rock, paper, scissors: harnessing complementarity in ortholog detection methods improves comparative genomic inference.
Bottom Line: OD methods comprise a wide variety of approaches, each with their own benefits and costs under a variety of evolutionary and practical scenarios.In head-to-head comparisons, we find that these algorithms significantly outperform one another for 38-45% of the genes analyzed.Further, this improvement in alignment quality yields more confidently aligned sites and higher levels of overall conservation, while simultaneously detecting of up to 180% more positively selected sites.
Affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, University of California, San Francisco, San Francisco, California.Show MeSH
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Mentions: We begin with a comprehensive comparison of four popular, methodologically distinct OD methods. In Figure 2, we show the head-to-head performances of these different methods for a range of primates and closely related mammals. Performance is assessed using alignments between all human consensus coding sequences (Pruitt et al. 2009) and their corresponding orthologs from each method. For each possible ortholog (defined by human target sequence and species of origin), we examine whether sequence identity to human is at least five percentage points greater for one method vs. another. We otherwise consider the two methods to be tied. By this metric, one method significantly outperforms another 38−45% of the time. Importantly, no method uniformly outperforms all others, underlining the complementarity of the chosen algorithms. For each method, distributions of percent identity and relative performance by species are presented in Figure S1 and Figure S2,
Affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, University of California, San Francisco, San Francisco, California.