Format

Send to

Choose Destination
Nat Biotechnol. 2015 Mar;33(3):290-5. doi: 10.1038/nbt.3122. Epub 2015 Feb 18.

StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.

Author information

1
1] Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland, USA. [2] McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
2
1] Department of Molecular Biology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA. [2] Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.
3
1] Department of Molecular Biology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA. [2] Center for Regenerative Science and Medicine, The University of Texas Southwestern Medical Center, Dallas, Texas, USA. [3] Simmons Cancer Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.
4
1] Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland, USA. [2] McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA. [3] Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA. [4] Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.

Abstract

Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.

PMID:
25690850
PMCID:
PMC4643835
DOI:
10.1038/nbt.3122
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center