TSUNAMI

TSUNAMI performs gene co-expression network (GCN) mining to identify tightly co-expressed gene modules for functional interpretation and correlation with clinical traits.

Key Features:

• Data integration: Direct access to GEO and TCGA and support for user-provided expression matrices from microarray, RNA-seq, or other numerical omics data.
• Advanced algorithmic approach: Implementation of the lmQCM algorithm to mine small, tightly connected, and potentially overlapping GCN modules suitable for downstream analysis.
• Co-expression analysis options: Multiple co-expression analysis methods with customizable parameter selection for tailored module detection.
• Eigengene summarization: Summarization of identified GCN modules into eigengenes to enable correlation with clinical traits.
• Integrated enrichment analysis: Downstream Gene Ontology and pathway enrichment using Enrichr and links to additional GO tools.
• Visualization: Generation of Circos plots for gene loci mapping at analysis steps.

Scientific Applications:

• Disease biomarker identification: Extraction of molecular features and modules associated with specific diseases or conditions.
• Gene function and pathway discovery: Detection of co-expressed gene sets to reveal novel gene functions and pathways.
• Drug target discovery: Identification of molecular interactions within gene modules that may suggest therapeutic targets.

Methodology:

Mining of GCN modules using the lmQCM algorithm; summarization of modules into eigengenes; GO and pathway enrichment analysis via Enrichr; generation of Circos plots for gene loci; supports input from GEO, TCGA, and user-provided microarray, RNA-seq, or other numerical omics expression matrices.