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Open Access Highly Accessed Software

iCTNet: A Cytoscape plugin to produce and analyze integrative complex traits networks

Lili Wang1, Pouya Khankhanian2, Sergio E Baranzini2* and Parvin Mousavi1

Author Affiliations

1 School of Computing, Queen's University. 25 Union Street, Goodwin Hall, Queen's University. Kingston, Ontario K7L 3N6, Canada

2 Department of Neurology, University of California San Francisco. 513 Parnassus Ave. Room S-256. San Francisco, CA, 94143. USA

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BMC Bioinformatics 2011, 12:380  doi:10.1186/1471-2105-12-380

Published: 26 September 2011

Abstract

Background

The speed at which biological datasets are being accumulated stands in contrast to our ability to integrate them meaningfully. Large-scale biological databases containing datasets of genes, proteins, cells, organs, and diseases are being created but they are not connected. Integration of these vast but heterogeneous sources of information will allow the systematic and comprehensive analysis of molecular and clinical datasets, spanning hundreds of dimensions and thousands of individuals. This integration is essential to capitalize on the value of current and future molecular- and cellular-level data on humans to gain novel insights about health and disease.

Results

We describe a new open-source Cytoscape plugin named iCTNet (

    i
ntegrated
    C
omplex
    T
raits
    Net
works). iCTNet integrates several data sources to allow automated and systematic creation of networks with up to five layers of omics information: phenotype-SNP association, protein-protein interaction, disease-tissue, tissue-gene, and drug-gene relationships. It facilitates the generation of general or specific network views with diverse options for more than 200 diseases. Built-in tools are provided to prioritize candidate genes and create modules of specific phenotypes.

Conclusions

iCTNet provides a user-friendly interface to search, integrate, visualize, and analyze genome-scale biological networks for human complex traits. We argue this tool is a key instrument that facilitates systematic integration of disparate large-scale data through network visualization, ultimately allowing the identification of disease similarities and the design of novel therapeutic approaches.

The online database and Cytoscape plugin are freely available for academic use at: http://www.cs.queensu.ca/ictnet webcite