SMITE

SMITE integrates transcriptional and epigenetic regulatory data to identify weighted gene modules and subnetworks that reflect altered cellular states.

Key Features:

• SpinGlass/iGraph module detection: Implements the SpinGlass algorithm via the iGraph package to identify weighted subnetworks or "modules" within genomic interaction networks.
• Integration without loss of resolution: Combines p-values from genome-wide assays while accounting for correlation between non-independent values to avoid initial pruning of data.
• Significance assignment: Assigns significance values to individual genes and to gene modules within interaction networks.
• Weighted data contribution: Permits weighting of different types of genomic data to integrate individually under-powered datasets into module-level signals.
• Scalability and assay flexibility: Accommodates diverse molecular assays testing gene expression, transcriptional regulation, and epigenetic regulation at genome scale.
• Epimods foundation: Builds upon the Epimods framework for integrating gene expression and epigenetic data.

Scientific Applications:

• Host–pathogen epigenomic/transcriptomic analysis: Applied to epigenomic and transcriptomic datasets of Toxoplasma gondii infection in human host cells to identify novel subnetworks of dysregulated genes.

Methodology:

Integrates p-values from complementary assays while accounting for correlation between non-independent values, assigns significance values to genes and gene modules, permits weighting of data types, and detects weighted subnetworks using the SpinGlass algorithm implemented in iGraph.