Gene Network Enrichment Analysis, Computational Genomics Lab, Boston University

Gene Network Enrichment Analysis (GNEA) is a network-based approach to the identification of transcriptionally altered biological processes between disease and normal states. It makes use of gene expression microarray data and protein-protein interaction information to identify transcriptionally affected regions of a protein-protein interaction network. Given sets of genes representing biological processes of interest, it then determines which of the gene sets are significantly over-represented in the identified regions. Significantly over-represented gene sets and associated biological processes are considered transcriptionally altered between the disease and normal states. To identify the transcriptionally affected regions of the protein-protein interaction network, GNEA uses the Cytoscape ActiveModules plugin. More information on the plugin can be found at the [Cytoscape plugins page].

The most recent distribution of GNEA available for download is 1.2. The download package is a gzipped, tar archive file and includes documentation, examples, and source code. [Download package]. This distribution changes some default flag values, fixes an occasional error when mapping from mouse to human gene symbols, and corrects incompatibilities with R 2.5.1.

Previous versions
[Version 1.0]

[Version 1.1]
This distribution fixes some incompatibilities with newer versions of R packages.

Manway Liu

The primary reference paper for GNEA 1.0 is Manway Liu, Arthur Liberzon, Sek Won Kong, Weil R. Lai, Peter J. Park, et al (2007) "Network-Based Analysis of Type 2 Diabetes" PLoS Genet. Jun 15;3(6):e96. and is available for download to the general public from PLoS Genetics, Pubmed Central, and [here].

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