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Nat Methods. 2015 Mar;12(3):211-4, 3 p following 214. doi: 10.1038/nmeth.3249. Epub 2015 Jan 12.

Targeted exploration and analysis of large cross-platform human transcriptomic compendia.

Author information

  • 11] Department of Computer Science, Princeton University, Princeton, New Jersey, USA. [2] Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • 2Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • 3Department of Genetics, Institute for Cancer Research, Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
  • 41] Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, USA. [2] Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
  • 51] Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA. [2] Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, New Hampshire, USA.
  • 6Department of Computer Science, University of Tromsø, Tromsø, Norway.
  • 71] Department of Genetics, Institute for Cancer Research, Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway. [2] Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway. [3] Department of Clinical Molecular Biology (EpiGen), Division of Medicine, Akershus University Hospital, Akershus, Norway.
  • 8Department of Computer Science, Princeton University, Princeton, New Jersey, USA.
  • 91] Department of Computer Science, Princeton University, Princeton, New Jersey, USA. [2] Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, New Jersey, USA. [3] Simons Center for Data Analysis, Simons Foundation, New York, New York, USA.

Abstract

We present SEEK (search-based exploration of expression compendia; http://seek.princeton.edu/), a query-based search engine for very large transcriptomic data collections, including thousands of human data sets from many different microarray and high-throughput sequencing platforms. SEEK uses a query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify genes, pathways and processes co-regulated with the query. SEEK provides multigene query searching with iterative metadata-based search refinement and extensive visualization-based analysis options.

PMID:
25581801
PMCID:
PMC4768301
DOI:
10.1038/nmeth.3249
[PubMed - indexed for MEDLINE]
Free PMC Article
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