Article

MissenseHMM: state-based annotations for missense variants through joint modeling of pathogenicity scores

2026-02-03

Abstract excerpt

Many computational predictors of missense variant pathogenicity are available. To capture information across various predictors, we propose MissenseHMM, which learns states corresponding to combinatorial patterns of variant prioritizations. We applied MissenseHMM to 43 predictors, annotating over 70 million missense variants with 20 states that showed distinct predictor scores patterns, amino acid substitutions an...

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Literature Corpus work: 5848a8a4-2e65-5490-b318-600a9c1c4e99
DOI: 10.64898/2026.01.31.703062

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