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deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index

The alignment of long-read RNA sequencing reads is non-trivial due to high sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass alignment approach, which constructs graph-based alignment skeletons to infer exons and uses them to generate spliced reference sequenc...

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Detalles Bibliográficos
Autores principales: Liu, Bo, Liu, Yadong, Li, Junyi, Guo, Hongzhe, Zang, Tianyi, Wang, Yadong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913027/
https://www.ncbi.nlm.nih.gov/pubmed/31842925
http://dx.doi.org/10.1186/s13059-019-1895-9
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author Liu, Bo
Liu, Yadong
Li, Junyi
Guo, Hongzhe
Zang, Tianyi
Wang, Yadong
author_facet Liu, Bo
Liu, Yadong
Li, Junyi
Guo, Hongzhe
Zang, Tianyi
Wang, Yadong
author_sort Liu, Bo
collection PubMed
description The alignment of long-read RNA sequencing reads is non-trivial due to high sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass alignment approach, which constructs graph-based alignment skeletons to infer exons and uses them to generate spliced reference sequences to produce refined alignments. deSALT addresses several difficult technical issues, such as small exons and sequencing errors, which break through bottlenecks of long RNA-seq read alignment. Benchmarks demonstrate that deSALT has a greater ability to produce accurate and homogeneous full-length alignments. deSALT is available at: https://github.com/hitbc/deSALT.
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spelling pubmed-69130272019-12-30 deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index Liu, Bo Liu, Yadong Li, Junyi Guo, Hongzhe Zang, Tianyi Wang, Yadong Genome Biol Method The alignment of long-read RNA sequencing reads is non-trivial due to high sequencing errors and complicated gene structures. We propose deSALT, a tailored two-pass alignment approach, which constructs graph-based alignment skeletons to infer exons and uses them to generate spliced reference sequences to produce refined alignments. deSALT addresses several difficult technical issues, such as small exons and sequencing errors, which break through bottlenecks of long RNA-seq read alignment. Benchmarks demonstrate that deSALT has a greater ability to produce accurate and homogeneous full-length alignments. deSALT is available at: https://github.com/hitbc/deSALT. BioMed Central 2019-12-16 /pmc/articles/PMC6913027/ /pubmed/31842925 http://dx.doi.org/10.1186/s13059-019-1895-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
Liu, Bo
Liu, Yadong
Li, Junyi
Guo, Hongzhe
Zang, Tianyi
Wang, Yadong
deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title_full deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title_fullStr deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title_full_unstemmed deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title_short deSALT: fast and accurate long transcriptomic read alignment with de Bruijn graph-based index
title_sort desalt: fast and accurate long transcriptomic read alignment with de bruijn graph-based index
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913027/
https://www.ncbi.nlm.nih.gov/pubmed/31842925
http://dx.doi.org/10.1186/s13059-019-1895-9
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