Article

Combining MAVEs and computational predictors improves variant classification across ancestries in hereditary cancer genes

2025-12-09

Abstract excerpt

Many commonly used computational tools for variant effect prediction exhibit ancestry-related bias because they are trained on clinical or population datasets that under-represent global diversity, leading to uneven and sometimes unfair variant classification across ancestries. Multiplexed assays of variant effect (MAVEs) and population-free VEPs instead offer alternatives that are unbiased with respect to human a...

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Literature Corpus work: 91a98376-250d-5086-914f-f699ae91142d
DOI: 10.64898/2025.12.08.25341119

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