Evidence map›Paper›PMID 39123290›Full record

ArticleClinical and translational science2024

Benchmarking pharmacogenomics genotyping tools: Performance analysis on short-read sequencing samples and depth-dependent evaluation.

Andreas Halman, Sebastian Lunke, Simon Sadedin, Claire Moore, Rachel Conyers

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. 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 · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andreas HalmanCancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Victoria, Australia.ORCID 0000-0001-5248-4121
Sebastian LunkeVictorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.ORCID 0000-0002-7168-0723
Simon SadedinVictorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.ORCID 0000-0002-2144-7894
Claire MooreCancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Victoria, Australia.ORCID 0000-0001-7253-7913
Rachel ConyersCancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Victoria, Australia.ORCID 0000-0002-2344-1365

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

BenchmarkingCytochrome P-450 CYP2D6PharmacogeneticsCytochrome P-450 CYP2A6Cytochrome P-450 CYP2C19Cytochrome P-450 CYP2C9GenotypeGenotyping TechniquesHigh-Throughput Nucleotide SequencingHumansPharmacogenomic TestingVitamin K Epoxide ReductasesWhole Genome SequencingCYP2A6 protein, humanCYP2C19 protein, humanCYP2C9 protein, humanCytochrome P-450 CYP2A6Cytochrome P-450 CYP2C19Cytochrome P-450 CYP2C9Cytochrome P-450 CYP2D6Vitamin K Epoxide ReductasesVKORC1 protein, human

Identifiers

PMID39123290
PMCPMC11315677

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.