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Supplemental Methods from TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal

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posted on 2023-03-31, 01:46 authored by Yulia Newton, Adam M. Novak, Teresa Swatloski, Duncan C. McColl, Sahil Chopra, Kiley Graim, Alana S. Weinstein, Robert Baertsch, Sofie R. Salama, Kyle Ellrott, Manu Chopra, Theodore C. Goldstein, David Haussler, Olena Morozova, Joshua M. Stuart

More detail into the methodology behind the resource are provided as well as proof-of-concept benchmarks.

Funding

National Cancer Institute

National Human Genome Research Institute

National Institute for General Medical Sciences

National Science Foundation Office of Cyberinfrastructure CAREER

Cancer – Prostate Cancer Foundation Prostate Dream Team

St. Baldricks Foundation Treehouse Childhood Cancer

California Kids Cancer Comparison

History

ARTICLE ABSTRACT

Vast amounts of molecular data are being collected on tumor samples, which provide unique opportunities for discovering trends within and between cancer subtypes. Such cross-cancer analyses require computational methods that enable intuitive and interactive browsing of thousands of samples based on their molecular similarity. We created a portal called TumorMap to assist in exploration and statistical interrogation of high-dimensional complex “omics” data in an interactive and easily interpretable way. In the TumorMap, samples are arranged on a hexagonal grid based on their similarity to one another in the original genomic space and are rendered with Google's Map technology. While the important feature of this public portal is the ability for the users to build maps from their own data, we pre-built genomic maps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. Cancer Res; 77(21); e111–4. ©2017 AACR.

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