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Bioinformatics. 2011 Nov 1;27(21):3010-6. doi: 10.1093/bioinformatics/btr508. Epub 2011 Sep 6.

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

Author information

1
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.

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 AS. Therefore, quantifying the inclusion level of every exon is crucial for generating accurate transcriptomic maps and studying the regulation of AS.

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.

PMID:
21896509
PMCID:
PMC3198574
DOI:
10.1093/bioinformatics/btr508
[Indexed for MEDLINE]
Free PMC Article

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