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Bioinformatics Strategies, Challenges, and Opportunities for Next Generation Sequencing-Based HLA Genotyping
Author(s) -
Klasberg Steffen,
Surendranath Vineeth,
Lange Vinzenz,
Schöfl Gerhard
Publication year - 2019
Publication title -
transfusion medicine and hemotherapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.971
H-Index - 39
eISSN - 1660-3818
pISSN - 1660-3796
DOI - 10.1159/000502487
Subject(s) - review article
AbstractThe advent of next generation sequencing (NGS) has altered the face of genotyping the human leukocyte antigen (HLA) system in clinical, stem cell donor registry, and research contexts. NGS has led to a dramatically increased sequencing throughput at high accuracy, while being more time and cost efficient than precursor technologies. This has led to a broader and deeper profiling of the key genes in the human immunogenetic make-up. The rapid evolution of sequencing technologies is evidenced by the development of varied short-read sequencing platforms with differing read lengths and sequencing capacities to long-read sequencing platforms capable of profiling full genes without fragmentation. Concomitantly, there has been development of a diverse set of computational analyses and software tools developed to deal with the various strengths and limitations of the sequencing data generated by the different sequencing platforms. This review surveys the different modalities involved in generating NGS HLA profiling sequence data. It systematically describes various computational approaches that have been developed to achieve HLA genotyping to different degrees of resolution. At each stage, this review enumerates the drawbacks and advantages of each of the platforms and analysis approaches, thus providing a comprehensive picture of the current state of HLA genotyping technologies.

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