ArticlePeerJ2017
phydms: software for phylogenetic analyses informed by deep mutational scanning.
Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Scanning the horizon: deep mutational scanning approaches in virology.Journal of virology · 2026Review
- Article
- Influenza hemagglutinin subtypes have different sequence constraints despite sharing extremely similar structures.bioRxiv : the preprint server for biology · 2026Article
- Comparative analysis of deep mutational scanning datasets in enteroviruses A and B identifies functional divergence and therapeutic targets.Nature ecology & evolution · 2026Article
- Influenza hemagglutinin subtypes have different sequence constraints despite sharing extremely similar structures.Virus evolution · 2026Article
- Separating selection from mutation in antibody language models.bioRxiv : the preprint server for biology · 2025Article
- Variant scoring tools for deep mutational scanning.Molecular systems biology · 2025Review
- Comparative Analysis of Deep Mutational Scanning Datasets in Enteroviruses A and B Identifies Functional Divergence and Therapeutic Targets.Research square · 2025Article
- Deep mutationally scanned CHIKV E3/E2 virus library maps viral amino acid preferences and predicts viral escape mutants of neutralizing CHIKV antibodies.Journal of virology · 2025Article
- Deep mutationally scanned (DMS) CHIKV E3/E2 virus library maps viral amino acid preferences and predicts viral escape mutants of neutralizing CHIKV antibodies.bioRxiv : the preprint server for biology · 2024Article
- Mapping mutational fitness effects across the coxsackievirus B3 proteome reveals distinct profiles of mutation tolerability.PLoS biology · 2024Article
- Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation.American journal of human genetics · 2023Article
- Systematically testing human HMBS missense variants to reveal mechanism and pathogenic variation.bioRxiv : the preprint server for biology · 2023Article
- Phylogenetic inference of changes in amino acid propensities with single-position resolution.PLoS computational biology · 2022Article
- Article
- Deep Mutational Scan of the Highly Conserved Influenza A Virus M1 Matrix Protein Reveals Substantial Intrinsic Mutational Tolerance.Journal of virology · 2019Article
- Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans.eLife · 2019Article
- Comprehensive profiling of translation initiation in influenza virus infected cells.PLoS pathogens · 2019Article
- Mechanisms and Concepts in RNA Virus Population Dynamics and Evolution.Annual review of virology · 2018Review
- Deep mutational scanning of hemagglutinin helps predict evolutionary fates of human H3N2 influenza variants.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
It has recently become possible to experimentally measure the effects of all amino-acid point mutations to proteins using deep mutational scanning. These experimental measurements can inform site-specific phylogenetic substitution models of gene evolution in nature. Here we describe software that efficiently performs analyses with such substitution models. This software, phydms, can be used to compare the results of deep mutational scanning experiments to the selection on genes in nature. Given a phylogenetic tree topology inferred with another program, phydms enables rigorous comparison of how well different experiments on the same gene capture actual natural selection. It also enables 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. As data from deep mutational scanning experiments become increasingly widespread, phydms will facilitate quantitative comparison of the experimental results to the actual selection pressures shaping evolution in nature.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.