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