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A Glioblastoma TCGA Data Visualizer

Tuesday, October 09, 2012 — Poster Session I

1:00 p.m. – 3:00 p.m

Natcher Conference Center, Building 45




  • O Celiku
  • K Camphausen
  • U Shankavaram


The Cancer Genome Atlas project has produced a wealth of multi-dimensional genomic data on various cancer. This has enabled a systems biology approach to investigating genetic and epigenetic changes responsible for cancer onset and progression, and response to cancer therapies. However, carrying out these analyses presently requires bulk downloads of data and substantial bioinformatics expertise, which can be intimidating for bench researchers and clinicians. We develop a free web-accessible resource for glioblastoma (GBM) TCGA data that enables intuitive querying and interactive displays of data. Stored experimental data include gene expression, micro RNA expression, DNA methylation, and mutation profiles of several hundred GBM samples. We also include data from computational predictions such as micro RNA targets, or molecular classification of GBM samples. Querying is organized around genes, micro RNAs, and clinical characteristics. A typical workflow involves investigation of differential expression of a gene in four molecular subtypes of GBM, and the impact of the gene expression level on patient survival. The results are displayed as histograms, barplots, and survival curves. Future work will extend the querying and visualization capabilities to enable integration of the data across the different types of experiments promoting a systems biology approach.

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