In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 6 ( 2022-6-1), p. e1009730-
Abstract:
Short-read RNA sequencing and long-read RNA sequencing each have their strengths and weaknesses for transcriptome assembly. While short reads are highly accurate, they are rarely able to span multiple exons. Long-read technology can capture full-length transcripts, but its relatively high error rate often leads to mis-identified splice sites. Here we present a new release of StringTie that performs hybrid-read assembly. By taking advantage of the strengths of both long and short reads, hybrid-read assembly with StringTie is more accurate than long-read only or short-read only assembly, and on some datasets it can more than double the number of correctly assembled transcripts, while obtaining substantially higher precision than the long-read data assembly alone. Here we demonstrate the improved accuracy on simulated data and real data from Arabidopsis thaliana , Mus musculus , and human. We also show that hybrid-read assembly is more accurate than correcting long reads prior to assembly while also being substantially faster. StringTie is freely available as open source software at https://github.com/gpertea/stringtie .
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1009730
DOI:
10.1371/journal.pcbi.1009730.g001
DOI:
10.1371/journal.pcbi.1009730.g002
DOI:
10.1371/journal.pcbi.1009730.g003
DOI:
10.1371/journal.pcbi.1009730.g004
DOI:
10.1371/journal.pcbi.1009730.g005
DOI:
10.1371/journal.pcbi.1009730.t001
DOI:
10.1371/journal.pcbi.1009730.s001
DOI:
10.1371/journal.pcbi.1009730.s002
DOI:
10.1371/journal.pcbi.1009730.s003
DOI:
10.1371/journal.pcbi.1009730.s004
DOI:
10.1371/journal.pcbi.1009730.s005
DOI:
10.1371/journal.pcbi.1009730.s006
DOI:
10.1371/journal.pcbi.1009730.s007
DOI:
10.1371/journal.pcbi.1009730.s008
DOI:
10.1371/journal.pcbi.1009730.s009
DOI:
10.1371/journal.pcbi.1009730.r001
DOI:
10.1371/journal.pcbi.1009730.r002
DOI:
10.1371/journal.pcbi.1009730.r003
DOI:
10.1371/journal.pcbi.1009730.r004
DOI:
10.1371/journal.pcbi.1009730.r005
DOI:
10.1371/journal.pcbi.1009730.r006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2193340-6
