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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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Related in: MedlinePlus

A comparison of evolutionary estimates. (A) The relative difference of MOSAICmatchedvs. each component method for: (1) the number of positively selected sites, (2) the number of confidently aligned sites, and for reference, (3) the average level of conservation across all alignments. (B) The agreement between positively selected sites (1) between MOSAIC and component methods, and (2) among component methods. Fractional overlap values are plotted as Venn diagrams to illustrate the two methods being compared.
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fig6: A comparison of evolutionary estimates. (A) The relative difference of MOSAICmatchedvs. each component method for: (1) the number of positively selected sites, (2) the number of confidently aligned sites, and for reference, (3) the average level of conservation across all alignments. (B) The agreement between positively selected sites (1) between MOSAIC and component methods, and (2) among component methods. Fractional overlap values are plotted as Venn diagrams to illustrate the two methods being compared.

Mentions: In Figure 6B, we see that MOSAIC leads to greater gene-level conservation (lower dN/dS) compared with every method except Blat, for which the difference was not statistically significant. Full distributions of dN/dS for each method are presented in Figure S7. Despite greater levels of conservation, MOSAIC was able to detect ~30–180% more positively selected sites than any of its component methods. This was not due to an increase in the inferred rate of positive selection. Rather, most of this increase in power was attributable to the fact that more sites were aligned to high confidence and therefore included in the analysis. This step of filtering for alignment quality is important because site-wise estimates of positive selection are highly sensitive to short poorly aligned regions (Jordan and Goldman 2012).


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

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

A comparison of evolutionary estimates. (A) The relative difference of MOSAICmatchedvs. each component method for: (1) the number of positively selected sites, (2) the number of confidently aligned sites, and for reference, (3) the average level of conservation across all alignments. (B) The agreement between positively selected sites (1) between MOSAIC and component methods, and (2) among component methods. Fractional overlap values are plotted as Venn diagrams to illustrate the two methods being compared.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig6: A comparison of evolutionary estimates. (A) The relative difference of MOSAICmatchedvs. each component method for: (1) the number of positively selected sites, (2) the number of confidently aligned sites, and for reference, (3) the average level of conservation across all alignments. (B) The agreement between positively selected sites (1) between MOSAIC and component methods, and (2) among component methods. Fractional overlap values are plotted as Venn diagrams to illustrate the two methods being compared.
Mentions: In Figure 6B, we see that MOSAIC leads to greater gene-level conservation (lower dN/dS) compared with every method except Blat, for which the difference was not statistically significant. Full distributions of dN/dS for each method are presented in Figure S7. Despite greater levels of conservation, MOSAIC was able to detect ~30–180% more positively selected sites than any of its component methods. This was not due to an increase in the inferred rate of positive selection. Rather, most of this increase in power was attributable to the fact that more sites were aligned to high confidence and therefore included in the analysis. This step of filtering for alignment quality is important because site-wise estimates of positive selection are highly sensitive to short poorly aligned regions (Jordan and Goldman 2012).

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