Assessment of transcript reconstruction methods for RNA-seq.

TitleAssessment of transcript reconstruction methods for RNA-seq.
Publication TypeJournal Article
Year of Publication2013
AuthorsSteijger T, Abril JF, Engström PG, Kokocinski F, Hubbard TJ, Guigó R, Harrow J, Bertone P
Corporate AuthorsRGASP Consortium
JournalNat Methods
Volume10
Issue12
Pagination1177-84
Date Published2013 Dec
ISSN1548-7105
KeywordsAlgorithms, Animals, Caenorhabditis elegans, Computational Biology, Drosophila melanogaster, Exons, Gene Expression Profiling, Genome, Humans, Introns, RNA Splice Sites, RNA Splicing, RNA, Messenger, Sequence Analysis, RNA, Software
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.

DOI10.1038/nmeth.2714
Alternate JournalNat Methods
PubMed ID24185837
PubMed Central IDPMC3851240
Grant ListU54HG004555 / HG / NHGRI NIH HHS / United States
WT098051 / WT_ / Wellcome Trust / United Kingdom
095908 / WT_ / Wellcome Trust / United Kingdom
077198 / WT_ / Wellcome Trust / United Kingdom
U54HG004557 / HG / NHGRI NIH HHS / United States
U54 HG004555 / HG / NHGRI NIH HHS / United States
U54 HG004557 / HG / NHGRI NIH HHS / United States
U41 HG007234 / HG / NHGRI NIH HHS / United States
/ WT_ / Wellcome Trust / United Kingdom
062023 / WT_ / Wellcome Trust / United Kingdom
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