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Rock, paper, scissors: harnessing complementarity in ortholog detection methods improves comparative genomic inference.

Maher MC, Hernandez RD - G3 (Bethesda) (2015)

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, University of California, San Francisco, San Francisco, California.

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MOSAIC improves alignment quality. We show the fold improvement of each method over the worst performing method in four categories: sequence identity, functional concordance, phylogenetic concordance, and number of orthologs detected.
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fig5: MOSAIC improves alignment quality. We show the fold improvement of each method over the worst performing method in four categories: sequence identity, functional concordance, phylogenetic concordance, and number of orthologs detected.

Mentions: With HMMER3, we queried protein sequences against all PfamA protein family profiles, annotating each protein according to its top protein family hit. This allowed for an ascertainment of functional concordance that is more comprehensive than relying on gene-by-gene annotation across species, while retaining many of the advantages of manual curation where it exists. This assessment reveals that, for the set of orthologous sequences proposed by all methods, MOSAIC provides levels of functional concordance that are slightly better than the best performing component method (Figure 5). Gains are particularly large for gorilla, bushbaby, and cat orthologs (Figure S4).


Rock, paper, scissors: harnessing complementarity in ortholog detection methods improves comparative genomic inference.

Maher MC, Hernandez RD - G3 (Bethesda) (2015)

MOSAIC improves alignment quality. We show the fold improvement of each method over the worst performing method in four categories: sequence identity, functional concordance, phylogenetic concordance, and number of orthologs detected.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4390578&req=5

fig5: MOSAIC improves alignment quality. We show the fold improvement of each method over the worst performing method in four categories: sequence identity, functional concordance, phylogenetic concordance, and number of orthologs detected.
Mentions: With HMMER3, we queried protein sequences against all PfamA protein family profiles, annotating each protein according to its top protein family hit. This allowed for an ascertainment of functional concordance that is more comprehensive than relying on gene-by-gene annotation across species, while retaining many of the advantages of manual curation where it exists. This assessment reveals that, for the set of orthologous sequences proposed by all methods, MOSAIC provides levels of functional concordance that are slightly better than the best performing component method (Figure 5). Gains are particularly large for gorilla, bushbaby, and cat orthologs (Figure S4).

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.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, University of California, San Francisco, San Francisco, California.

Show MeSH
Related in: MedlinePlus