Student and Faculty Publications
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
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetics Commons, Medical Genetics Commons, Oncology Commons
Comments
Supplementary Materials
PMID: 37490908