Evidence map›Paper›PMID 39763645›Full record

ArticleFrontiers in immunology2024

Geny: a genotyping tool for allelic decomposition of killer cell immunoglobulin-like receptor genes.

Qinghui Zhou, Mazyar Ghezelji, Ananth Hari, Michael K B Ford, Connor Holley, S Cenk Sahinalp, Ibrahim Numanagić

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Qinghui Zhou *Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Mazyar Ghezelji *Department of Computer Science, University of Victoria, Victoria, BC, Canada.
Ananth HariDepartment of Electrical Engineering, University of Maryland, College Park, MD, United States.
Michael K B FordNational Cancer Institute, NIH, Bethesda, MD, United States.
Connor HolleyDepartment of Computer Science, University of Victoria, Victoria, BC, Canada.
S Cenk SahinalpNational Cancer Institute, NIH, Bethesda, MD, United States.
Ibrahim NumanagićDepartment of Computer Science, University of Victoria, Victoria, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the generic genotyping workflows are unable to accurately infer copy numbers and complete genotypes of individual KIR genes from next-generation sequencing data. Thus, specialized genotyping tools are needed to genotype this complex region. Methods: Here, we introduce Geny, a new computational tool for precise genotyping of KIR genes. Geny utilizes available KIR allele databases and proposes a novel combination of expectation-maximization filtering schemes and integer linear programming-based combinatorial optimization models to resolve ambiguous reads, provide accurate copy number estimation, and estimate the correct allele of each copy of genes within the KIR region. Results & Discussion: We evaluated Geny on a large set of simulated short-read datasets covering the known validated KIR region assemblies and a set of Illumina short-read samples sequenced from 40 validated samples from the Human Pangenome Reference Consortium collection and showed that it outperforms the existing state-of-the-art KIR genotyping tools in terms of accuracy, precision, and recall. We envision Geny becoming a valuable resource for understanding immune system response and consequently advancing the field of patient-centric medicine.

Indexed as

AllelesGenotypeGenotyping TechniquesReceptors, KIRComputational BiologyHigh-Throughput Nucleotide SequencingHumansSoftwareReceptors, KIRbioinformaticscombinatorial optimizationcomputational biologygenotypingKIRsoftware

Identifiers

PMID39763645
PMCPMC11701374

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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.