ArticleMolecular biology and evolution2022
PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations.
Article in Molecular biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Prediction of human missense variant effects from functional evidence.Nature genetics · 2026Article
- GraphyloVar: predicting the impact of non-coding variants using a multi-species sequence model.Bioinformatics (Oxford, England) · 2026Article
- PHACE: Phylogeny-Aware Detection of Molecular Coevolution.Molecular biology and evolution · 2025Article
- Variant effect predictor correlation with functional assays is reflective of clinical classification performance.Genome biology · 2025Article
- Assessing predictions on fitness effects of missense variants in HMBS in CAGI6.Human genetics · 2025Article
- Complementary Roles of Structure and Variant Effect Predictors in RyR1 Clinical Interpretation.Human mutation · 2025Article
- Evolutionary history of calcium-sensing receptors unveils hyper/hypocalcemia-causing mutations.PLoS computational biology · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- PHACTboost: A Phylogeny-Aware Pathogenicity Predictor for Missense Mutations via Boosting.Molecular biology and evolution · 2024Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone-without considering the evolutionary relationships among sequences-results in the redundant counting of evolutionarily related alteration events, as if they were independent. Here, we propose a new method, PHACT, that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3,023 proteins and 61,662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved a better predictive performance than other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT.
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