ArticleNature methods2013
Assessment of transcript reconstruction methods for RNA-seq.
Article in Nature methods, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 415 papers.
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Who cites it
415 citing papers in PubMed.
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- From fragments to full pictures: how long-read sequencing platforms are revolutionizing oncology research.Molecular biology reports · 2026Review
- The circadian isoform landscape of mouse livers.NAR genomics and bioinformatics · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- Transcriptome assemblies for two drug-type cannabis chemotypes by long-read RNA sequencing.The plant genome · 2026Article
- Long-read transcriptomics of purified human cortical cell types exposes glial isoform complexity and disease-relevant transcript architecture.bioRxiv : the preprint server for biology · 2026Article
- Efficient reconstruction of full-length RNA isoforms using ISAtools and large-scale PacBio circular consensus sequencing data.Briefings in bioinformatics · 2026Article
- Proteoform medicine: characterizing and targeting protein forms in human disease.Nature reviews. Genetics · 2026Review
- Population-scale interpretation of RNA isoform diversity enabled by Isopedia.bioRxiv : the preprint server for biology · 2026Article
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- A systematic PCR-based framework for amplification of long and multi-exonic genes in non-model insects: : A case study of Bemisia tabaci Asia II 1.Molecular biology reports · 2026Article
- Article
355 more citing papers are in PubMed but not listed here.
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9 authors.
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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.
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