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

Larsson Omberg, Kyle Ellrott, Yuan Yuan, Cyriac Kandoth, Chris Wong, Michael R. Kellen, Stephen H. Friend, Josh Stuart, Han Liang, Adam A. Margolin

Research output: Contribution to journalReview article

64 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1121-1126
Number of pages6
JournalNature genetics
Volume45
Issue number10
DOIs
StatePublished - Oct 2013

ASJC Scopus subject areas

  • Genetics

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    Omberg, L., Ellrott, K., Yuan, Y., Kandoth, C., Wong, C., Kellen, M. R., Friend, S. H., Stuart, J., Liang, H., & Margolin, A. A. (2013). Enabling transparent and collaborative computational analysis of 12 tumor types within the Cancer Genome Atlas. Nature genetics, 45(10), 1121-1126. https://doi.org/10.1038/ng.2761