Background The evolution of protein-coding genes can be quantitatively modeled using phylogenetic methods. Recently, it has been shown that high-throughput experimental measurements of mutational effects made via deep mutational scanning can inform site-specific phylogenetic substitution models of gene evolution. However, there is currently no software tailored for such analyses. Results We describe software that efficiently performs phylogenetic analyses with substitution models informed by deep mutational scanning. This software, phydms, is ∼100-fold faster than existing programs that accommodate such substitution models. It can be used to compare the results of deep mutational scanning experiments to the selection on genes in nature. For instance, phydms enables rigorous comparison of how well different experiments on the same gene describe natural selection. It also enables the re-scaling of deep mutational scanning data to account for differences in the stringency of selection in the lab and nature. Finally, phydms can identify sites that are evolving differently in nature than expected from experiments in the lab. Conclusions The phydms software makes it easy to use phylogenetic substitution models informed by deep mutational scanning experiments. As data from such experiments becomes increasingly widespread, phydms will facilitate quantitative comparison of the experimental results to the actual selection pressures shaping evolution in nature.
phydms: software for phylogenetic analyses informed by deep mutational scanning
Sarah K. Hilton,Michael B. Doud,J. Bloom
Published 2017 in bioRxiv
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- Publication year
2017
- Venue
bioRxiv
- Publication date
2017-03-29
- Fields of study
Biology, Medicine, Computer Science
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Semantic Scholar, PubMed
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