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.

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See further information about this publication at the following links:

• Large-scale assessment of transcriptome analysis software (EBI).
• The companion paper on evaluation of spliced alignment programs for RNA-seq data:
       Engström, et al. Systematic evaluation of spliced alignment programs for RNA-seq data. Nature Methods, 10(12):1185-1191, 2013.