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TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal
Yulia Newton1, Adam M Novak1, Teresa Swatloski1
1Department of Biomolecular Engineering and Bioinformatics, University of California, Santa Cruz, California.
Cancer Research
|November 3, 2017
Summary
TumorMap is a new portal that helps researchers explore complex cancer molecular data. It visually organizes thousands of tumor samples by similarity, aiding in the discovery of cancer subtype trends.
Area of Science:
- Computational biology
- Genomics
- Cancer research
Background:
- Increasing amounts of molecular data from tumor samples offer opportunities for cross-cancer analyses.
- Analyzing this high-dimensional data requires intuitive computational methods for exploring sample similarity.
Purpose of the Study:
- To develop a portal, TumorMap, for interactive exploration and statistical analysis of complex, high-dimensional cancer omics data.
- To enable researchers to intuitively browse and understand molecular similarities across thousands of tumor samples.
Main Methods:
- Developed TumorMap, a web portal utilizing Google Maps technology.
- Samples are arranged on a hexagonal grid based on genomic similarity.
- Users can build custom maps or utilize pre-built maps from published projects.
Main Results:
- Demonstrated the utility of TumorMap using data from The Cancer Genome Atlas (TCGA).
- The portal facilitates interactive exploration and statistical interrogation of complex omics data.
- Pre-built maps from several projects are available for immediate use.
Conclusions:
- TumorMap provides an accessible and interpretable platform for exploring large-scale cancer molecular data.
- The portal supports cross-cancer analyses by visualizing sample similarity.
- Facilitates discovery of trends within and between cancer subtypes.
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