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Article

Benchmarking computational variant effect predictors by their ability to infer human traits.

Genome biology - 1 Jul 2024

Tabet Daniel R, Kuang Da, Lancaster Megan C, Li Roujia, Liu Karen, Weile Jochen, Coté Atina G, Wu Yingzhou, Hegele Robert A, Roden Dan M, Roth Frederick P

Abstract excerpt

BACKGROUND: Computational 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...

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Identifiers

PMID: 38951922
DOI: 10.1186/s13059-024-03314-7
PMCID: PMC11218265

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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