GSCA

GSCA performs gene set cancer analysis by integrating expression, mutation, drug sensitivity, tumor immune infiltration, and clinical data consolidated from four public sources across 33 cancer types to enable multi-omics gene set-level discovery.

Key Features:

• Integrated Multi-Omics Data: Consolidates expression, mutation, drug sensitivity, tumor immune infiltration, and clinical datasets from four public sources across 33 cancer types.
• Functional Modules: Provides dedicated modules for expression analysis, genomic variation exploration, tumor immune infiltration assessment, and drug sensitivity evaluation at the gene set level.
• Gene Set Analysis (GSA): Applies Gene Set Analysis methods to enhance signal-to-noise ratio and derive biological insights at the gene set level.
• Clinical Outcome Associations: Evaluates associations between gene set expression or mutation patterns and clinical outcomes to identify gene set-level correlations.
• Case Study Validation: Has been applied to gene sets including cell cycle genes, PI3K pathway tumor suppressor genes, and PI3K pathway oncogenes to reveal associations not apparent in single-gene analyses.

Scientific Applications:

• Pathway Dysregulation Identification: Identify dysregulated biological pathways involved in cancer initiation and progression.
• Genomic–Immune–Pharmacogenomic Interplay: Explore relationships among genetic variation, immune cell infiltration, and drug sensitivity at the gene set level.
• Clinical Association Discovery: Discover novel gene set-level associations with clinical outcomes across diverse cancer types.

Methodology:

Performs Gene Set Analysis (GSA) and advanced GSA methods to conduct hypothesis-driven tests across integrated expression, mutation, drug sensitivity, tumor immune infiltration, and clinical datasets consolidated from four public sources covering 33 cancer types.