Cyrius: accurate CYP2D6 genotyping using whole genome sequencing data

Abstract

Responsible for the metabolism of 25% of all drugs, CYP2D6 is a critical component of personalized medicine initiatives. Genotyping CYP2D6 is challenging due to sequence similarity with its pseudogene paralog CYP2D7 and a high number and variety of common structural variants (SVs). Here we describe a novel bioinformatics method, Cyrius, that accurately genotypes CYP2D6 using whole-genome sequencing (WGS) data. Using a validation data set consisting of reference samples with diverse genotypes as well as PacBio long read data, we show that Cyrius has superior performance (96.5% concordance with truth genotypes) compared to existing methods (83.8-86.6%). After implementing the improvements identified from the comparison against the truth data, Cyrius’s accuracy has since been improved to 99.3%. Using Cyrius, we built a haplotype frequency database from 2504 ethnically diverse samples and estimate that SV-containing star alleles are more frequent than previously reported. Cyrius will be a useful tool for pharmacogenomics applications with WGS and help bring the promise of precision medicine one step closer to reality.