Format

Send to:

Choose Destination
See comment in PubMed Commons below
Nat Genet. 2015 Jun;47(6):569-76. doi: 10.1038/ng.3259. Epub 2015 Apr 27.

Understanding multicellular function and disease with human tissue-specific networks.

Author information

  • 11] Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA. [2] Dartmouth-Hitchcock Norris Cotton Cancer Center, Lebanon, New Hampshire, USA. [3] Institute for Quantitative Biomedical Sciences, Dartmouth College, Hanover, New Hampshire, USA.
  • 2Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.
  • 3Department of Computer Science, Princeton University, Princeton, New Jersey, USA.
  • 41] Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA. [2] Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • 5Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.
  • 6Biology and Medical Informatics, University of California, San Francisco, San Francisco, California, USA.
  • 7Department of Molecular Biology, Princeton University, Princeton, New Jersey, USA.
  • 8Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • 9Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
  • 101] Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA. [2] Department of Computer Science, Princeton University, Princeton, New Jersey, USA. [3] Simons Center for Data Analysis, Simons Foundation, New York, New York, USA.

Abstract

Tissue and cell-type identity lie at the core of human physiology and disease. Understanding the genetic underpinnings of complex tissues and individual cell lineages is crucial for developing improved diagnostics and therapeutics. We present genome-wide functional interaction networks for 144 human tissues and cell types developed using a data-driven Bayesian methodology that integrates thousands of diverse experiments spanning tissue and disease states. Tissue-specific networks predict lineage-specific responses to perturbation, identify the changing functional roles of genes across tissues and illuminate relationships among diseases. We introduce NetWAS, which combines genes with nominally significant genome-wide association study (GWAS) P values and tissue-specific networks to identify disease-gene associations more accurately than GWAS alone. Our webserver, GIANT, provides an interface to human tissue networks through multi-gene queries, network visualization, analysis tools including NetWAS and downloadable networks. GIANT enables systematic exploration of the landscape of interacting genes that shape specialized cellular functions across more than a hundred human tissues and cell types.

Comment in

PMID:
25915600
[PubMed - indexed for MEDLINE]
PMCID:
PMC4828725
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Nature Publishing Group Icon for PubMed Central
    Loading ...
    Write to the Help Desk