OptiType: precision HLA typing from next-generation sequencing data

The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity wi...

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Bibliographic Details
Published inBioinformatics Vol. 30; no. 23; pp. 3310 - 3316
Main Authors Szolek, András, Schubert, Benjamin, Mohr, Christopher, Sturm, Marc, Feldhahn, Magdalena, Kohlbacher, Oliver
Format Journal Article
LanguageEnglish
Published England Oxford University Press 01.12.2014
Subjects
Algorithms
Antigens
Bioinformatics
Clusters
Enrichment
Exome
Genotyping Techniques
High-Throughput Nucleotide Sequencing - methods
Histocompatibility Testing - methods
HLA Antigens - genetics
Humans
Introns
Original Papers
Patients
Sequence Analysis, DNA - methods
Sequencing
Similarity
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Summary:The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci. Established approaches, therefore, rely on specific HLA enrichment and sequencing techniques, coming at an additional cost and extra turnaround time. We present OptiType, a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. We also present a comprehensive benchmark dataset consisting of RNA, exome and whole-genome sequencing data. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications.
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Associate Editor: Michael Brudno
The authors wish it to be known that, in their opinion, the first three authors should be regarded as Joint First Authors.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btu548