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Supplemental Figure 5 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

Supplemental Figure 5: (A) Overview of the method to compute differential expression for samples in the integrated pan-cancer group vs. other samples in the TCGA cohort. Tissue composition imbalance was corrected for by performing t-tests within each tissue. For each gene, t-statistics were computed within each tumor type separately and then summarized per-gene t-statistics were calculated as an arithmetic mean, weighted by the inverse variance of the all the tissue-specific t-statistics values. (B) The distribution of log-transformed TPM values estimated from the mRNA-Seq data showing a normal-like distribution. (C) Comparing the log-transformed TPM values of the mRNA-Seq data to a normal distribution shows a reasonable agreement with the tumor data having slightly heavier tails. (D) Venn diagram representing the innate and adaptive immune systems and different levels of evidence supporting higher activity of each of the components of those systems in the pan-cancer cluster when compared to the rest of the TCGA cohort. We found evidence of both innate and adaptive immune system signaling with a number of different analyses. (E) Detailed version of the immune-related pathway characterizing the integrated pan-cancer cluster. This version of the pathway shows additional genes and their connections that are not shown in the summarized version of the immune signaling pathway of Figure 1D of the main text.

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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