Genotype error due to low-coverage sequencing induces uncertainty in polygenic scoring.

ABSTRACT: Polygenic scores (PGSs) have emerged as a standard approach to predict phenotypes from genotype data in a wide array of applications from socio-genomics to personalized medicine. Traditional PGSs assume genotype data to be error-free, ignoring possible errors and uncertainties introduced from genotyping, sequencing, and/or imputation. In this work, we investigate the effects of genotyping error due to low coverage sequencing on PGS estimation. We leverage SNP array and low-coverage whole-genome sequencing data (lcWGS, median coverage 0.04×) of 802 individuals from the Dana-Farber PROFILE cohort to show that PGS error correlates with sequencing depth (p = 1.2 × 10^-7). We develop a probabilistic approach that incorporates genotype error in PGS estimation to produce well-calibrated

SUBMITTER: Petter E 

PROVIDER: S-EPMC10432141 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature