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Andras Szolek, Benjamin Schubert, Christopher Mohr, Marc Sturm, Magdalena Feldhahn, and Oliver Kohlbacher (2014)

OptiType: precision HLA typing from next-generation sequencing data

Bioinformatics, 30(23):3310-6.

Motivation: 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 is often available for a patient, deducing the HLA genotype is difficult due to 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. Result: 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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25143287
10.1093/bioinformatics/btu548