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

delete2017-10-31
delete60
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OA
AI
Y
Yulia Newton
N
Novak, Adam M.
T
Teresa Swatloski
D
Duncan C. McColl
S
Sahil Chopra
K
Kiley Graim
A
Alana S. Weinstein
R
Robert Baertsch
S
Sofie R. Salama
K
Kyle Ellrott
M
M. R. Chopra
T
Theodore C. Goldstein
D
David Haussler
O
Olena Morozova
J
Joshua M. Stuart *
DOI:10.1158/0008-5472.CAN-17-0580delete
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Abstract

Abstract

En 中文
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 interpret-able 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 owndata, we pre-built genomicmaps from several previously published projects. We demonstrate the utility of this portal by presenting results obtained from The Cancer Genome Atlas project data. (C) 2017 AACR.
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Journal

Cancer Research cover
Cancer Research
IF:
16.6
Papers:
10.9W
Citations:
11.9W

Organization

University of California System cover
University of California System
Scholars:
37.2W
Papers: 33.6W
Citations: 6.6K