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HLAscan: genotyping of the HLA region using next-generation sequencing data, BMC Bioinformatics (201…

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작성자 관리자 작성일2017-05-25 조회21,420회


Sojeong Ka[1] , Sunho Lee[2] , Jonghee Hong[3] , Yangrae Cho[4] , Joohon Sung[5] Han-Na Kim[6]  Hyung-Lae Kim[7]  and Jongsun Jung[8]


[1] [3] R&D center, Syntekabio, Inc.
[2] [4] [8] Main office, Syntekabio, Inc.
[5] Complex Disease and Genome Epidemiology Branch, Department of Epidemiology, School of Public Health, Seoul National University
[6] [7]Department of Biochemistry, School of Medicine, Ewha Womans University


Background: Several recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data.

Results: HLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, −B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing–based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, −B, −C, −DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%.

Conclusions: HLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.

Conclusions: Morphological AML subtypes may in part reflect subtype specific patterns of genomic alterations. Following validation, future studies to evaluate the usefulness of these genes in genetic testing for the early diagnosis and prognostic prediction of AML patients would be worthwhile.

Keywords: HLA-typing-Next-generation sequencing-Phasing issue-HLAscan

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