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Bioinformatics Strategies Challenges and Opportunities for Next Generation Sequencing-Based HLA Genotyping

机译:基于下一代测序的HLA基因分型的生物信息学策略挑战和机遇

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摘要

The 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.
机译:下一代测序(NGS)的出现改变了在临床,干细胞供体登记和研究背景下对人类白细胞抗原(HLA)系统进行基因分型的面貌。 NGS大大提高了高精度测序的通量,同时比先驱技术节省了时间和成本。这导致了人类免疫遗传结构中关键基因的更广泛和更深入的分析。测序技术的飞速发展是由具有不同阅读长度和测序能力的各种短读测序平台的发展证明的,而长读测序平台却能够分析完整的基因而无片段化。随之而来的是,已经开发出各种计算分析和软件工具,以应对由不同测序平台生成的测序数据的各种优势和局限性。这篇综述调查了生成NGS HLA分析序列数据所涉及的不同模式。它系统地描述了为实现HLA基因分型到不同程度的分辨率而开发的各种计算方法。在每个阶段,本文都将列举每种平台和分析方法的弊端和优势,从而全面了解HLA基因分型技术的现状。

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