TCGASpliceSeq a compendium of alternative mRNA splicing in cancer

Michael Ryan1, Wing Chung Wong2, Robert Brown2

  • 1Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA In Silico Solutions, Falls Church, VA 22043, USA mryan@insilico.us.com.

Nucleic Acids Research
|November 26, 2015
PubMed

Insights

TCGA SpliceSeq offers a user-friendly web interface to explore cancer alternative mRNA splicing patterns using RNASeq data. This resource visualizes splicing variations across 33 tumor types, aiding cancer research.

Area of Science:

  • Genomics and Bioinformatics
  • Cancer Transcriptomics
  • Molecular Biology

Background:

  • The Cancer Genome Atlas (TCGA) provides extensive RNASeq data for cancer transcriptomes.
  • Alternative mRNA splicing is crucial in cancer development, including carcinogenesis, de-differentiation, and metastasis.
  • Understanding splicing alterations is vital for cancer research.

Purpose of the Study:

  • To develop TCGA SpliceSeq, a web-based resource for exploring alternative splicing patterns in TCGA tumors.
  • To provide a user-friendly, visual interface for analyzing splicing data.
  • To enable investigation of splicing variations between tumor types and between tumors and adjacent normal tissues.

Main Methods:

  • Utilized TCGA RNASeq data for 33 different tumor types.
  • Developed the SpliceSeq computational package and a web-based interface.
  • Loaded Percent Spliced In (PSI) values for splice events and associated statistical summaries.

Main Results:

  • TCGA SpliceSeq offers a highly visual and intuitive interface for exploring splicing patterns.
  • Users can interrogate specific genes, identify genes with significant splicing variation, or compare tumor vs. normal samples.
  • Splicing data, including PSI values and graphical representations, are accessible and downloadable.

Conclusions:

  • TCGA SpliceSeq is a valuable, freely accessible resource for the cancer research community.
  • Facilitates in-depth analysis of alternative splicing in cancer using TCGA data.
  • Supports integrative analyses and discovery of novel splicing-related cancer mechanisms.