Genotype Error Due to Low-Coverage Sequencing Induces Uncertainty in Polygenic Scoring

Authors

Ella Petter
Yi Ding
Kangcheng Hou
Arjun Bhattacharya
Alexander Gusev
Noah Zaitlen
Bogdan Pasaniuc

Publication Date

8-3-2023

Journal

American Journal of Human Genetics

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

Keywords

Uncertainty, Genotype, Genomics, Whole Genome Sequencing, Polymorphism, Single Nucleotide

Comments

Supplementary Material

PMID: 37490908

DOI

10.1016/j.ajhg.2023.06.015

PMID

37490908

PMCID

PMC10432141

PubMedCentral® Posted Date

July 2023

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes