American Association for Cancer Research
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Supplemental Figure 3 from TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal

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journal contribution
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

Tissue and molecular subtype distribution among the samples in the entire cohort (A-B), and in the pan-cancer cluster (C-D). The pie charts represent the number of samples from each tissue of origin in the entire cohort (A) and the integrated pan-cancer cluster (C). Black and white matrices illustrate the presence of molecular features of each platform (x-axis) across samples (y-axis), in the entire cohort (B) or in the integrated pan-cancer cluster (D). Data available for this sample for a given platform is marked black, otherwise the entry is white.


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



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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