title: OptiType: precision HLA typing from next-generation sequencing data.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  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.
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: András
authors.initials: A
authors.lastname: Szolek
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Schubert
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: Christopher
authors.initials: C
authors.lastname: Mohr
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Sturm
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: Magdalena
authors.initials: M
authors.lastname: Feldhahn
authors.affiliation: Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Department of Computer Science, University of Tübingen, Institute of Medical Genetics and Applied Genomics, University of Tübingen, and CeGaT GmbH, 72076 Tübingen, Germany.
authors.forename: Oliver
authors.initials: O
authors.lastname: Kohlbacher
mesh_terms: D000465:Algorithms; D059472:Exome; D060005:Genotyping Techniques; D006680:HLA Antigens / Q000235:genetics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006650:Histocompatibility Testing / Q000379:methods*; D006801:Humans; D007438:Introns; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D006680:HLA Antigens