ArticleStatistics in biosciences2013
Statistical and Computational Methods for High-Throughput Sequencing Data Analysis of Alternative Splicing.
Article in Statistics in biosciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Systematic evaluation of differential splicing tools for RNA-seq studies.Briefings in bioinformatics · 2020Article
- Comparisons of computational methods for differential alternative splicing detection using RNA-seq in plant systems.BMC bioinformatics · 2014Article
- FineSplice, enhanced splice junction detection and quantification: a novel pipeline based on the assessment of diverse RNA-Seq alignment solutions.Nucleic acids research · 2014Article
- Gene set enrichment analysis of RNA-Seq data: integrating differential expression and splicing.BMC bioinformatics · 2013Article
- IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity.Journal of the American Statistical AssociationArticle
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
The burgeoning field of high-throughput sequencing significantly improves our ability to understand the complexity of transcriptomes. Alternative splicing, as one of the most important driving forces for transcriptome diversity, can now be studied at an unprecedent resolution. Efficient and powerful computational and statistical methods are in urgent need to facilitate the characterization and quantification of alternative splicing events. Here we discuss methods in splice junction read mapping, and methods in exon-centric or isoform-centric quantification of alternative splicing. In addition, we discuss HITS-CLIP and splicing QTL analyses which are novel high-throughput sequencing based approaches in the dissection of splicing regulation.
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Registered trials
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