Format

Send to

Choose Destination
Nat Methods. 2013 Dec;10(12):1177-84. doi: 10.1038/nmeth.2714. Epub 2013 Nov 3.

Assessment of transcript reconstruction methods for RNA-seq.

Author information

1
European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK.
2
Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain.
3
Wellcome Trust Sanger Institute, Cambridge, UK.
4
Center for Genomic Regulation, Barcelona, Spain.
5
Universitat Pompeu Fabra, Barcelona, Spain.
6
Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
7
Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
8
Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK.
#
Contributed equally

Abstract

We evaluated 25 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression-level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression-level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations on transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.

PMID:
24185837
PMCID:
PMC3851240
DOI:
10.1038/nmeth.2714
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

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