Evidence map›Paper›PMID 36657977›Full record

ArticleGenome research2023

An efficient genotyper and star-allele caller for pharmacogenomics.

Ananth Hari, Qinghui Zhou, Nina Gonzaludo, John Harting, Stuart A Scott, Xiang Qin, Steve Scherer, S Cenk Sahinalp, Ibrahim Numanagić

Abstract read
In one paragraph

Article in Genome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
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  5. Review
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  9. PharmVar GeneFocus: NAT2-Genetic Variation and Updated Nomenclature.Clinical pharmacology and therapeutics · 2026
    Review
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  11. Article
  12. Article
  13. Article
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  16. Population-scale Long-read Sequencing in themedRxiv : the preprint server for health sciences · 2025
    Article
  17. Article
  18. Article
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  20. 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

9 authors.

Ananth HariDepartment of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742, USA.
Qinghui ZhouDepartment of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada.
Nina GonzaludoPacific Biosciences, Menlo Park, California 94025, USA.
John HartingPacific Biosciences, Menlo Park, California 94025, USA.
Stuart A ScottDepartment of Pathology, Stanford University, Palo Alto, California 94304, USA.ORCID 0000-0001-5720-1864
Xiang QinBaylor College of Medicine Human Genome Sequencing Center, Houston, Texas 77030, USA.
Steve SchererBaylor College of Medicine Human Genome Sequencing Center, Houston, Texas 77030, USA.
S Cenk SahinalpCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.
Ibrahim NumanagićDepartment of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada.ORCID 0000-0002-2970-7937

Funding

Tumor evolution and intratumor heterogeneityZIABC011987 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI SAHINALP, SULEYMAN · 2020 to 2025
$6.6M
6 · The paper itself

Abstract

High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.

Indexed as

PharmacogeneticsPolymorphism, Single NucleotideAllelesGenomicsGenotypeHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID36657977
PMCPMC9977157

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Registered trials

None linked

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.