ArticleBMC bioinformatics2013
Estimation of data-specific constitutive exons with RNA-Seq data.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Quantifying transcriptome diversity: a review.Briefings in functional genomics · 2024Review
- McSplicer: a probabilistic model for estimating splice site usage from RNA-seq data.Bioinformatics (Oxford, England) · 2021Article
- Pathway analysis for RNA-Seq data using a score-based approach.Biometrics · 2016Article
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3 authors.
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Abstract
backgroundRNA-Seq has the potential to answer many diverse and interesting questions about the inner workings of cells. Estimating changes in the overall transcription of a gene is not straightforward. Changes in overall gene transcription can easily be confounded with changes in exon usage which alter the lengths of transcripts produced by a gene. Measuring the expression of constitutive exons--xons which are consistently conserved after splicing--ffers an unbiased estimation of the overall transcription of a gene.
resultsWe propose a clustering-based method, exClust, for estimating the exons that are consistently conserved after splicing in a given data set. These are considered as the exons which are "constitutive" in this data. The method utilises information from both annotation and the dataset of interest. The method is implemented in an openly available R function package, sydSeq.
conclusionWhen used on two real datasets exClust includes more than three times as many reads as the standard UI method, and improves concordance with qRT-PCR data. When compared to other methods, our method is shown to produce robust estimates of overall gene transcription.
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