iNETgrate

iNETgrate integrates DNA methylation and gene expression data to build a correlation network in which nodes are genes, identifies modules of genes, and represents each module's biological information by an eigengene for use as robust biological signatures.

Key Features:

• Multi-omics integration: DNA methylation and gene expression data are integrated to define connections between genes in the network.
• Module detection: The network is used to identify modules (clusters) of genes.
• Eigengene representation: The biological information in each module is represented by an eigengene.
• Robust signature generation: The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.

Scientific Applications:

• Patient risk classification: Biological signatures can be used as features for classification of patients into risk categories.

Methodology:

iNETgrate builds a correlation network with genes as nodes, integrates DNA methylation and gene expression data to define gene-gene connections, identifies gene modules, and represents each module by an eigengene.