Summary: SpliceSeq is a resource for RNA-Seq data that provides a clear view of alternative splicing and identifies potential functional changes that result from splice variation. It displays intuitive visualizations and prioritized lists of results that highlight splicing events and their biological consequences. SpliceSeq unambiguously aligns reads to gene splice graphs, facilitating accurate analysis of large, complex transcript variants that cannot be adequately represented in other formats.
Availability And Implementation: SpliceSeq is freely available at http://bioinformatics.mdanderson.org/main/SpliceSeq:Overview. The application is a Java program that can be launched via a browser or installed locally. Local installation requires MySQL and Bowtie.
Contact: mryan@insilico.us.com
Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/bts452 | DOI Listing |
Nucleic Acids Res
January 2016
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
TCGA's RNASeq data represent one of the largest collections of cancer transcriptomes ever assembled. RNASeq technology, combined with computational tools like our SpliceSeq package, provides a comprehensive, detailed view of alternative mRNA splicing. Aberrant splicing patterns in cancers have been implicated in such processes as carcinogenesis, de-differentiation and metastasis.
View Article and Find Full Text PDFBioinformatics
September 2012
In Silico Solutions, Fairfax, VA, USA.
Summary: SpliceSeq is a resource for RNA-Seq data that provides a clear view of alternative splicing and identifies potential functional changes that result from splice variation. It displays intuitive visualizations and prioritized lists of results that highlight splicing events and their biological consequences. SpliceSeq unambiguously aligns reads to gene splice graphs, facilitating accurate analysis of large, complex transcript variants that cannot be adequately represented in other formats.
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