Analysis of missense variants in the human genome reveals widespread gene-specific clustering and improves prediction of pathogenicity.

ABSTRACT: We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (46%) and 172 (20%) genes, respectively, revealing that variant clustering is widespread across the human exome. This clustering likely occurs as a consequence of mechanisms shaping pathogenicity at the protein level, as illustrated by the overlap of some clusters with known functional domains. We then took advantage of these findings to develop a pathogenicity predictor, MutScore, that integrates qualitative features of DNA substitutions with the new additional information derived from this posit

SUBMITTER: Quinodoz M 

PROVIDER: S-EPMC8948164 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature