Transcriptome assembly from long-read RNA-seq alignments with StringTie2

Abstract RNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome asse...

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Main Authors: Sam Kovaka, Aleksey V. Zimin, Geo M. Pertea, Roham Razaghi, Steven L. Salzberg, Mihaela Pertea
Format: Article
Language:English
Published: BMC 2019-12-01
Series:Genome Biology
Subjects:
Online Access:https://doi.org/10.1186/s13059-019-1910-1
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author Sam Kovaka
Aleksey V. Zimin
Geo M. Pertea
Roham Razaghi
Steven L. Salzberg
Mihaela Pertea
author_facet Sam Kovaka
Aleksey V. Zimin
Geo M. Pertea
Roham Razaghi
Steven L. Salzberg
Mihaela Pertea
author_sort Sam Kovaka
collection DOAJ
description Abstract RNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new methods to handle the high error rate of long reads and offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of short-read assemblies. StringTie2 is more accurate and faster and uses less memory than all comparable short-read and long-read analysis tools.
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spelling doaj.art-a59b453d2b4541c696e1a12aa19c7e0d2022-12-21T19:58:08ZengBMCGenome Biology1474-760X2019-12-0120111310.1186/s13059-019-1910-1Transcriptome assembly from long-read RNA-seq alignments with StringTie2Sam Kovaka0Aleksey V. Zimin1Geo M. Pertea2Roham Razaghi3Steven L. Salzberg4Mihaela Pertea5Department of Computer Science, Johns Hopkins UniversityCenter for Computational Biology, Whiting School of Engineering, Johns Hopkins UniversityCenter for Computational Biology, Whiting School of Engineering, Johns Hopkins UniversityCenter for Computational Biology, Whiting School of Engineering, Johns Hopkins UniversityDepartment of Computer Science, Johns Hopkins UniversityCenter for Computational Biology, Whiting School of Engineering, Johns Hopkins UniversityAbstract RNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new methods to handle the high error rate of long reads and offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of short-read assemblies. StringTie2 is more accurate and faster and uses less memory than all comparable short-read and long-read analysis tools.https://doi.org/10.1186/s13059-019-1910-1Transcriptome assemblyRNA-seqLong-read sequencingGene expression
spellingShingle Sam Kovaka
Aleksey V. Zimin
Geo M. Pertea
Roham Razaghi
Steven L. Salzberg
Mihaela Pertea
Transcriptome assembly from long-read RNA-seq alignments with StringTie2
Genome Biology
Transcriptome assembly
RNA-seq
Long-read sequencing
Gene expression
title Transcriptome assembly from long-read RNA-seq alignments with StringTie2
title_full Transcriptome assembly from long-read RNA-seq alignments with StringTie2
title_fullStr Transcriptome assembly from long-read RNA-seq alignments with StringTie2
title_full_unstemmed Transcriptome assembly from long-read RNA-seq alignments with StringTie2
title_short Transcriptome assembly from long-read RNA-seq alignments with StringTie2
title_sort transcriptome assembly from long read rna seq alignments with stringtie2
topic Transcriptome assembly
RNA-seq
Long-read sequencing
Gene expression
url https://doi.org/10.1186/s13059-019-1910-1
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