gCMAP

gCMAP constructs and queries connectivity maps from differential microarray and RNA-seq gene expression data to link disease phenotypes with chemical and genetic perturbations.

Key Features:

• Standardized Data Processing: Processes microarray and RNA-seq data in a standardized manner to enable consistent comparison of differential expression profiles across datasets.
• Differential Expression Analysis: Performs differential expression analysis to identify genes with significant changes between experimental conditions.
• Connectivity Map Construction and Querying: Constructs and queries connectivity maps that capture relationships among perturbations and differential gene-expression profiles to identify common patterns induced by chemical or genetic perturbations.
• Gene Set Enrichment Analysis: Supports multiple gene set enrichment methods to analyze connectivity maps and identify affected biological processes or pathways.
• User-Defined Connectivity Maps: Enables construction of connectivity maps from user-provided collections of differential gene expression data.

Scientific Applications:

• Drug Discovery and Repositioning: Compares disease-state expression profiles with compound- or perturbation-induced profiles to identify agents producing similar or opposite transcriptional effects for therapeutic prioritization.
• Phenotype–Perturbation Mapping: Elucidates connections between disease phenotypes and chemical or genetic perturbations by identifying shared transcriptional signatures.

Methodology:

Users provide normalized microarray or RNA-seq gene expression data (including global differential expression profiles or specific experiments); the software performs differential expression analysis; constructs connectivity maps from the processed data; and analyzes the maps using gene set enrichment methods and querying of map relationships.