Accurate assignment of disease liability to genetic variants using only population data.

ABSTRACT:

Purpose

The growing size of public variant repositories prompted us to test the accuracy of pathogenicity prediction of DNA variants using population data alone.

Methods

Under the a priori assumption that the ratio of the prevalence of variants in healthy population vs that in affected populations form 2 distinct distributions (pathogenic and benign), we used a Bayesian method to assign probability to a variant belonging to either distribution.

Results

The approach, termed Bayesian prevalence ratio (BayPR), accurately parsed 300 of 313 expertly curated CFTR variants: 284 of 296 pathogenic/likely pathogenic variants in 1 distribution and 16 of 17 benign/likely benign variants in another. BayPR produced an area under the receiver operating characteristic curve of 0.99 f

SUBMITTER: Collaco JM 

PROVIDER: S-EPMC10280479 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature