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

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

doi:10.1016/j.ajhg.2023.06.015

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

Am J Hum Genet. 2023 Aug 3;110(8):1319-1329. doi: 10.1016/j.ajhg.2023.06.015. Epub 2023 Jul 24.

Authors

Ella Petter¹, Yi Ding², Kangcheng Hou², Arjun Bhattacharya³, Alexander Gusev⁴, Noah Zaitlen⁵, Bogdan Pasaniuc⁶

Affiliations

¹ Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: ellapetter@ucla.edu.
² Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA.
³ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁴ Dana-Farber Cancer Institute, Boston, MA, USA; Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
⁵ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Neurology, UCLA, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
⁶ Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: pasaniuc@ucla.edu.

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 PGS credible intervals and show that the probabilistic approach increases classification accuracy by up to 6% as compared to traditional PGSs that ignore genotyping error. Finally, we use simulations to explore the combined effect of genotyping and effect size errors and their implication on PGS-based risk-stratification. Our results illustrate the importance of considering genotyping error as a source of PGS error especially for cohorts with varying genotyping technologies and/or low-coverage sequencing.

Keywords: PGS; PGS error; effect sizes; genotype error; lcWGS; risk stratification; uncertainty.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Genomics* / methods
Genotype
Polymorphism, Single Nucleotide* / genetics
Uncertainty
Whole Genome Sequencing

Abstract

Publication types

MeSH terms

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