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

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 us...

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Vydané v:	Nature biotechnology Ročník 37; číslo 8; s. 907 - 915
Hlavní autori:	Kim, Daehwan, Paggi, Joseph M, Park, Chanhee, Bennett, Christopher, Salzberg, Steven L
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Nature Publishing Group 01.08.2019
Predmet:	Alignment Base Sequence Benchmarking Computer applications Computer simulation Data structures Deoxyribonucleic acid DNA DNA fingerprinting Gene sequencing Genetic fingerprinting Genetic Variation Genome, Human Genomes Genomics Genotype Genotype & phenotype Genotypes Genotyping Haplotypes Histocompatibility antigen HLA Humans Nucleotide sequence Reproducibility of Results Ribonucleic acid RNA Search algorithms Sequence Analysis, DNA - methods Sequence Analysis, RNA - methods Software Tissue typing
ISSN:	1087-0156, 1546-1696, 1546-1696
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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.
AbstractList	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. 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.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.
Author	Park, Chanhee Paggi, Joseph M Salzberg, Steven L Bennett, Christopher Kim, Daehwan
Author_xml	– sequence: 1 givenname: Daehwan orcidid: 0000-0003-1182-629X surname: Kim fullname: Kim, Daehwan email: daehwan.kim@utsouthwestern.edu organization: Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA. daehwan.kim@utsouthwestern.edu – sequence: 2 givenname: Joseph M surname: Paggi fullname: Paggi, Joseph M organization: Department of Computer Science, Stanford University, Stanford, CA, USA – sequence: 3 givenname: Chanhee surname: Park fullname: Park, Chanhee organization: Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA – sequence: 4 givenname: Christopher orcidid: 0000-0003-3329-2567 surname: Bennett fullname: Bennett, Christopher organization: Lyda Hill Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX, USA – sequence: 5 givenname: Steven L orcidid: 0000-0002-8859-7432 surname: Salzberg fullname: Salzberg, Steven L organization: Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, MD, USA
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/31375807$$D View this record in MEDLINE/PubMed
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Snippet	The human reference genome represents only a small number of individuals, which limits its usefulness for genotyping. We present a method named HISAT2...
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SubjectTerms	Alignment Base Sequence Benchmarking Computer applications Computer simulation Data structures Deoxyribonucleic acid DNA DNA fingerprinting Gene sequencing Genetic fingerprinting Genetic Variation Genome, Human Genomes Genomics Genotype Genotype & phenotype Genotypes Genotyping Haplotypes Histocompatibility antigen HLA Humans Nucleotide sequence Reproducibility of Results Ribonucleic acid RNA Search algorithms Sequence Analysis, DNA - methods Sequence Analysis, RNA - methods Software Tissue typing
Title	Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype
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