TumorMap

Exploring the molecular similarities of cancer samples in an interactive portal

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

Research output: Contribution to journalArticle

10 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)e111-e114
JournalCancer Research
Volume77
Issue number21
DOIs
StatePublished - Nov 1 2017

Fingerprint

Neoplasms
Atlases
Genome
Technology

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Newton, Y., Novak, A. M., Swatloski, T., McColl, D. C., Chopra, S., Graim, K., ... Stuart, J. M. (2017). TumorMap: Exploring the molecular similarities of cancer samples in an interactive portal. Cancer Research, 77(21), e111-e114. https://doi.org/10.1158/0008-5472.CAN-17-0580

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.

In: Cancer Research, Vol. 77, No. 21, 01.11.2017, p. e111-e114.

Research output: Contribution to journalArticle

Newton, Y, Novak, AM, Swatloski, T, McColl, DC, Chopra, S, Graim, K, Weinstein, AS, Baertsch, R, Salama, SR, Ellrott, K, Chopra, M, Goldstein, TC, Haussler, D, Morozova, O & Stuart, JM 2017, 'TumorMap: Exploring the molecular similarities of cancer samples in an interactive portal', Cancer Research, vol. 77, no. 21, pp. e111-e114. https://doi.org/10.1158/0008-5472.CAN-17-0580
Newton Y, Novak AM, Swatloski T, McColl DC, Chopra S, Graim K et al. TumorMap: Exploring the molecular similarities of cancer samples in an interactive portal. Cancer Research. 2017 Nov 1;77(21):e111-e114. https://doi.org/10.1158/0008-5472.CAN-17-0580
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. / TumorMap : Exploring the molecular similarities of cancer samples in an interactive portal. In: Cancer Research. 2017 ; Vol. 77, No. 21. pp. e111-e114.
@article{6da73d93642f4e7abd7905b964aeef0f,
title = "TumorMap: Exploring the molecular similarities of cancer samples in an interactive portal",
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.",
author = "Yulia Newton and Novak, {Adam M.} and Teresa Swatloski and McColl, {Duncan C.} and Sahil Chopra and Kiley Graim and Weinstein, {Alana S.} and Robert Baertsch and Salama, {Sofie R.} and Kyle Ellrott and Manu Chopra and Goldstein, {Theodore C.} and David Haussler and Olena Morozova and Stuart, {Joshua M.}",
year = "2017",
month = "11",
day = "1",
doi = "10.1158/0008-5472.CAN-17-0580",
language = "English (US)",
volume = "77",
pages = "e111--e114",
journal = "Journal of Cancer Research",
issn = "0099-7013",
publisher = "American Association for Cancer Research Inc.",
number = "21",

}

TY - JOUR

T1 - TumorMap

T2 - Exploring the molecular similarities of cancer samples in an interactive portal

AU - Newton, Yulia

AU - Novak, Adam M.

AU - Swatloski, Teresa

AU - McColl, Duncan C.

AU - Chopra, Sahil

AU - Graim, Kiley

AU - Weinstein, Alana S.

AU - Baertsch, Robert

AU - Salama, Sofie R.

AU - Ellrott, Kyle

AU - Chopra, Manu

AU - Goldstein, Theodore C.

AU - Haussler, David

AU - Morozova, Olena

AU - Stuart, Joshua M.

PY - 2017/11/1

Y1 - 2017/11/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85035028333&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85035028333&partnerID=8YFLogxK

U2 - 10.1158/0008-5472.CAN-17-0580

DO - 10.1158/0008-5472.CAN-17-0580

M3 - Article

VL - 77

SP - e111-e114

JO - Journal of Cancer Research

JF - Journal of Cancer Research

SN - 0099-7013

IS - 21

ER -