美国德克萨斯大学西南医学中心Daehwan Kim研究团队提出一种快速精确的运算程序名为HISAT2，该程序可以较好完成基因组比对和分型工作。 该研究成果于2019年8月发表于国际学术期刊《自然—生物技术》上。

该课题组研究人员提出了一种名为HISAT2（hierarchical indexing for spliced alignment of transcripts 2）的方法，该方法使用一种图像性Ferragina Manzini指数来比对DNA和RNA序列。研究人员使用HISAT2去检索拥有超过1450万个基因组变异并结合单倍型的人类基因组数据库来检测其搜索和比对功能，结果显示HISAT2比其他方法能够更加全面和准确的完成变异分析。然后，将HISAT2应用于HLA分型和DNA指纹去分析单倍型解析的基因或基因组区域，得到优质的结果。

据悉人类参考基因组仅代表少数个体，这限制了它在基因分型中的作用。

附：英文原文

Title: Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

Author: Daehwan Kim, Joseph M. Paggi, Chanhee Park, Christopher Bennett, Steven L. Salzberg

Issue&Volume: Volume 37 Issue 8

Abstract: The human reference genome represents only a small number of individuals, which limits its usefulness for genotyping. We present a method named HISAT2 (hierarchical indexing for spliced alignment of transcripts 2) that can align both DNA and RNA sequences using a graph Ferragina Manzini index. We use HISAT2 to represent and search an expanded model of the human reference genome in which over 14.5 million genomic variants in combination with haplotypes are incorporated into the data structure used for searching and alignment. We benchmark HISAT2 using simulated and real datasets to demonstrate that our strategy of representing a population of genomes, together with a fast, memory-efficient search algorithm, provides more detailed and accurate variant analyses than other methods. We apply HISAT2 for HLA typing and DNA fingerprinting; both applications form part of the HISAT-genotype software that enables analysis of haplotype-resolved genes or genomic regions. HISAT-genotype outperforms other computational methods and matches or exceeds the performance of laboratory-based assays.

DOI: 10.1038/s41587-019-0201-4

Source:https://www.nature.com/articles/s41587-019-0201-4