ArticleGenome biology2024
Benchmarking computational variant effect predictors by their ability to infer human traits.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- MultimodalCirculation · 2026Article
- A heritability-optimized method for functional prioritization of rare coding variants in complex traits.Nature genetics · 2026Article
- From conservation scores to language models: a feature engineering perspective on machine learning for genetic variant interpretation.Briefings in bioinformatics · 2026Review
- Gene- and domain-aware calibration increases the clinical utility of variant effect predictors.Research square · 2026Article
- Feed-Forward Deep Neural Networks Predict Substrate-Specific Effects of Transporter Variants to Explain Drug Response Variability.Clinical and translational science · 2026Article
- Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine.Nature reviews. Cardiology · 2026Review
- The functional landscape of coding variation in the familial hypercholesterolemia geneScience (New York, N.Y.) · 2026Article
- Predicting Pathogenicity ofInternational journal of molecular sciences · 2026Article
- Predicting the functional impact of single nucleotide variants in Drosophila melanogaster with FlyCADD.Genetics · 2026Article
- Genetic architecture and phenotypic diversity of oocyte and early embryo competence defects in female infertility.Nature medicine · 2026Article
- Reclassification of missense variant pathogenicity using ClinGen recommendations for recalibrated PP3/BP4 in silico predictor score thresholds.Genetics in medicine open · 2026Article
- Mapping the Functional Landscape ofmedRxiv : the preprint server for health sciences · 2025Article
- Assessing the performance of 28 pathogenicity prediction methods on rare single nucleotide variants in coding regions.BMC genomics · 2025Article
- Large-scale experimental assessment of variant effects on the structure and function of the citrate transporter SLC13A5.Science advances · 2025Article
- Leveraging protein structural information to improve variant effect prediction.Current opinion in structural biology · 2025Review
- Variant effect predictor correlation with functional assays is reflective of clinical classification performance.Genome biology · 2025Article
- Guidelines for releasing a variant effect predictor.Genome biology · 2025Article
- Language Modelling Techniques for Analysing the Impact of Human Genetic Variation.Bioinformatics and biology insights · 2025Review
- Functional Screen of Wilson Disease ATP7B Variants Reveals Residual Transport Activities.Human mutation · 2025Article
- Benchmarking of variant pathogenicity prediction methods using a population genetics approach.Bioinformatics advances · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundComputational variant effect predictors offer a scalable and increasingly reliable means of interpreting human genetic variation, but concerns of circularity and bias have limited previous methods for evaluating and comparing predictors. Population-level cohorts of genotyped and phenotyped participants that have not been used in predictor training can facilitate an unbiased benchmarking of available methods. Using a curated set of human gene-trait associations with a reported rare-variant burden association, we evaluate the correlations of 24 computational variant effect predictors with associated human traits in the UK Biobank and All of Us cohorts.
resultsAlphaMissense outperformed all other predictors in inferring human traits based on rare missense variants in UK Biobank and All of Us participants. The overall rankings of computational variant effect predictors in these two cohorts showed a significant positive correlation.
conclusionWe describe a method to assess computational variant effect predictors that sidesteps the limitations of previous evaluations. This approach is generalizable to future predictors and could continue to inform predictor choice for personal and clinical genetics.
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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.