ArticleClinical and translational science2024
Benchmarking pharmacogenomics genotyping tools: Performance analysis on short-read sequencing samples and depth-dependent evaluation.
Article in Clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Characterization of NAT2 Using Long-Read Sequencing: Allele, Diplotype, and Phenotype Call Accuracy Compared to Other Testing Strategies.Clinical pharmacology and therapeutics · 2026Article
- Benchmark of Open-Access Star-Allele Callers to Accurately Assess Haplotypes and Phenotypes in Pharmacogenetic Studies.Clinical pharmacology and therapeutics · 2026Article
- Genotoxicity of cancer therapies and the risk of secondary malignancies: toward personalized prevention.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Frequency and Implications of High-Risk Pharmacogenomic Phenotypes Identified in a Diverse Australian Pediatric Oncology Cohort.Clinical and translational science · 2025Article
- Phenoconversion of CYP3A4, CYP2C19 and CYP2D6 in Pediatrics, Adolescents and Young Adults With Lymphoma: Rationale and Design of the PEGASUS Study.Clinical and translational science · 2025Article
- StarPhase: Comprehensive Phase-Aware Pharmacogenomic Diplotyper for Long-Read Sequencing Data.bioRxiv : the preprint server for biology · 2024Article
- Benchmarking pharmacogenomics genotyping tools: Performance analysis on short-read sequencing samples and depth-dependent evaluation.Clinical and translational science · 2024Article
- Practical guide to implementing pre-emptive pharmacogenetic screening in routine pediatric oncology care.PharmacogenomicsArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pharmacogenomics (PGx) investigates the influence of genetics on drug responses, enabling tailored treatments for personalized healthcare. This study assessed the accuracy of genotyping six genes using whole genome sequencing with four different computational tools and various sequencing depths. The effects of using different reference genomes (GRCh38 and GRCh37) and sequence aligners (BWA-MEM and Bowtie2) were also explored. The results showed generally minor variations in tool performance across most genes; however, more notable discrepancies were observed in the analysis of the complex CYP2D6 gene. Cyrius, a CYP2D6-specific tool, demonstrated the most robust performance, achieving the highest concordance rates for CYP2D6 in all instances, comparable to the consensus approach in most cases. There were rather small differences between the samples with 20× coverage depth and those with higher depth, but the decreased performance was more evident at lower depths, particularly at 5×. Additionally, variations in CYP2D6 results were observed when samples were aligned to different reference genomes using the same method, or to the same genome using different aligners, which led to reporting incorrect rare star alleles in several cases. These findings inform the selection of optimal PGx tools and methodologies as well as suggest that employing a consensus approach with two or more tools might be preferable for certain genes and tool combinations, especially at lower sequencing depths, to ensure accurate results. Additionally, we show how the upstream alignment can affect the performance of tools, an important factor to take into account.
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