Gene Network Enrichment Analysis (GNEA)

Submitted by on Jun 18 2014 } Suggest Revision
By: Manway Liu
From: Boston University
Resource Type:
Code
License:
Framework/Library
Language:
R
Data Format:

Description

Aims to identify biological processes that are consistently deregulated across a broad set of microarray experiments associated with different disease models in both animal and human tissues. GNEA consists of five steps: (1) Assemble a collection of gene sets associated with biological processes or signalling pathways of interest (2) Assume an underlying model of cellular processes using a global protein–protein interaction network (3) Evaluate the hypothesis that genes in a given gene set are observed in a higher proportion (i.e., enriched) than expected by chance in the high-scoring subnetwork (HSN) and repeat for each gene set in the assembly (4) Order the gene sets of interest based on the number of different HSNs where they appear enriched (5) For each gene set, assign a p-value to the number of conditions where it is enriched.
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