SpliceTrap: a method to quantify alternative splicing under single cellular conditions

Wu, J., Akerman, M., Sun, S., McCombie, W. R., Krainer, A. R., Zhang, M. Q. (2011) SpliceTrap: a method to quantify alternative splicing under single cellular conditions. Bioinformatics, 27 (21). 3010-3016 . ISSN 1367-4803

URL: http://www.ncbi.nlm.nih.gov/pubmed/21896509
DOI: 10.1093/bioinformatics/btr508

Abstract

MOTIVATION: Alternative Splicing (AS) is a pre-mRNA maturation process leading to the expression of multiple mRNA variants from the same primary transcript. More than 90% of human genes are expressed via alternative splicing. Therefore, quantifying the inclusion level of every exon is crucial for generating accurate transcriptomic maps and studying the regulation of alternative splicing. RESULTS: Here we introduce SpliceTrap, a method to quantify exon inclusion levels using paired-end RNA-seq data. Unlike other tools, which focus on full-length transcript isoforms, SpliceTrap approaches the expression-level estimation of each exon as an independent Bayesian inference problem. In addition, SpliceTrap can identify major classes of alternative splicing events under a single cellular condition, without requiring a background set of reads to estimate relative splicing changes. We tested SpliceTrap both by simulation and real data analysis, and compared it to state-of-the-art tools for transcript quantification. SpliceTrap demonstrated improved accuracy, robustness, and reliability in quantifying exon-inclusion ratios.Conclusions: SpliceTrap is a useful tool to study alternative splicing regulation, especially for accurate quantification of local exon-inclusion ratios from RNA-seq data.Availability and implementation: SpliceTrap can be implemented online through the CSH Galaxy server http://cancan.cshl.edu/splicetrap and is also available for download and installation at http://rulai.cshl.edu/splicetrap/. CONTACT: michael.zhang@utdallas.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > exons > exon splicing
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > RNA splicing
CSHL Authors:
Communities: CSHL Cancer Center Program > Gene Regulation and Cell Proliferation
CSHL Cancer Center Shared Resources > Bioinformatics Service
CSHL Post Doctoral Fellows
CSHL labs > Krainer lab
CSHL labs > McCombie lab
CSHL Cancer Center Program > Cancer Genetics
Depositing User: Matt Covey
Date Deposited: 05 Feb 2013 14:35
Last Modified: 15 Oct 2015 15:15
PMCID: PMC3198574
Related URLs:
URI: http://repository.cshl.edu/id/eprint/27217

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