Assessment of transcript reconstruction methods for RNA-seq

Tamara Steijger(European Bioinformatics Institute), Josep F. Abril(Universitat de Barcelona), Pär G. Engström(European Bioinformatics Institute), Felix Kokocinski(Wellcome Sanger Institute), Tim Hubbard(Wellcome Sanger Institute), Roderic Guigó(Universitat Pompeu Fabra), Jennifer Harrow(Wellcome Sanger Institute), Paul Bertone(European Bioinformatics Institute)
Nature Methods
November 3, 2013
Cited by 769Open Access
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Abstract

The RGASP consortium compared 25 RNA-seq analysis programs in their ability to identify exons, reconstruct transcripts and quantify expression levels. Assembly of isoforms and their expression levels in higher eukaryotes remains a challenge. 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.


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