Assessment of transcript reconstruction methods for RNA-seq.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 24185837.
- Also identified by DOI 10.1038/nmeth.2714 and PMC identifier 3851240.
- Licence recorded as CC BY-NC-SA.
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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.
Medical subject headings
- Computational Biology
- RNA Splicing
- Sequence Analysis, RNA