Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas

The Cancer Genome Atlas Pan-Cancer Analysis Working Group collaborated on the Synapse software platform to share and evolve data, results and methodologies while performing integrative analysis of molecular profiling data from 12 tumor types. The group’s work serves as a pilot case study that provid...

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Autores principales: Omberg, Larsson, Ellrott, Kyle, Yuan, Yuan, Kandoth, Cyriac, Wong, Chris, Kellen, Michael R, Friend, Stephen H, Stuart, Josh, Liang, Han, Margolin, Adam A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950337/
https://www.ncbi.nlm.nih.gov/pubmed/24071850
http://dx.doi.org/10.1038/ng.2761
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author Omberg, Larsson
Ellrott, Kyle
Yuan, Yuan
Kandoth, Cyriac
Wong, Chris
Kellen, Michael R
Friend, Stephen H
Stuart, Josh
Liang, Han
Margolin, Adam A
author_facet Omberg, Larsson
Ellrott, Kyle
Yuan, Yuan
Kandoth, Cyriac
Wong, Chris
Kellen, Michael R
Friend, Stephen H
Stuart, Josh
Liang, Han
Margolin, Adam A
author_sort Omberg, Larsson
collection PubMed
description The Cancer Genome Atlas Pan-Cancer Analysis Working Group collaborated on the Synapse software platform to share and evolve data, results and methodologies while performing integrative analysis of molecular profiling data from 12 tumor types. The group’s work serves as a pilot case study that provides (i) a template for future large collaborative studies; (ii) a system to support collaborative projects; and (iii) a public resource of highly curated data, results and automated systems for the evaluation of community-developed models.
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spelling pubmed-39503372014-03-12 Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas Omberg, Larsson Ellrott, Kyle Yuan, Yuan Kandoth, Cyriac Wong, Chris Kellen, Michael R Friend, Stephen H Stuart, Josh Liang, Han Margolin, Adam A Nat Genet Article The Cancer Genome Atlas Pan-Cancer Analysis Working Group collaborated on the Synapse software platform to share and evolve data, results and methodologies while performing integrative analysis of molecular profiling data from 12 tumor types. The group’s work serves as a pilot case study that provides (i) a template for future large collaborative studies; (ii) a system to support collaborative projects; and (iii) a public resource of highly curated data, results and automated systems for the evaluation of community-developed models. 2013-10 /pmc/articles/PMC3950337/ /pubmed/24071850 http://dx.doi.org/10.1038/ng.2761 Text en © 2013 Nature America, Inc. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
spellingShingle Article
Omberg, Larsson
Ellrott, Kyle
Yuan, Yuan
Kandoth, Cyriac
Wong, Chris
Kellen, Michael R
Friend, Stephen H
Stuart, Josh
Liang, Han
Margolin, Adam A
Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title_full Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title_fullStr Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title_full_unstemmed Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title_short Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas
title_sort enabling transparent and collaborative computational analysis of 12 tumor types within the cancer genome atlas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950337/
https://www.ncbi.nlm.nih.gov/pubmed/24071850
http://dx.doi.org/10.1038/ng.2761
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