Supplemental Figure 1 from TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal

Newton, Yulia; Novak, Adam M.; Swatloski, Teresa; McColl, Duncan C.; Chopra, Sahil; Graim, Kiley; Weinstein, Alana S.; Baertsch, Robert; Salama, Sofie R.; Ellrott, Kyle; Chopra, Manu; Goldstein, Theodore C.; Haussler, David; Morozova, Olena; Stuart, Joshua M.

doi:10.1158/0008-5472.22419039.v1

Supplemental Figure 1 from TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal

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

Supplemental Figure 1: RSS transformed correlations correct for platform-specific inflation biases. Maps produced from different molecular data types. Samples in the maps are colored by tissue of origin. (A) Similarity score distributions for every pair of samples for each individual data platform. Spearman Rho was computed for mRNA, miRNA, RPPA, SCNV, and methylation platforms. HOCUS score was used for mutation data. (B) RSS-standardized similarity scores for every pair of samples for each individual data platform. The density curves demonstrate that RSS transformation corrects for platform-specific inflation biases. (C) (i)-(vi) Maps produced from each of the six molecular data types using OpenOrd layout. (vii) mRNA expression map produced using Principal Component Analysis method. Principal components 1 and 2 are used to represent the mRNA expression space. (viii) mRNA expression map produced using tSNE method. Dimensions 1 and 2 are used to represent the mRNA expression space. (D) Maps produced from inferred gene activities using the PARADIGM and SPIA methods. (E) Maps integrating more than one molecular data type.

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.