cBioPortal

cBioPortal provides access to and enables analysis of molecular profiles and clinical attributes from over 5,000 tumor samples and cell lines across more than 20 cancer studies to support integrative cancer genomics and translational research.

Key Features:

• Dataset coverage: Access to molecular profiles and clinical attributes derived from over 5,000 tumor samples and cell lines across more than 20 distinct cancer studies.
• Multi-omics event distillation: Distills molecular profiling data into genetic, epigenetic, gene expression, and proteomic events.
• Genetic alteration queries: Exploration of genetic alterations across samples, genes, and pathways with linkage to clinical outcomes when available.
• Graphical summaries: Generation of graphical summaries of gene-level data from multiple platforms.
• Network visualization and analysis: Visualization and analysis of molecular interaction networks and pathway relationships.
• Survival analysis: Analytical capability to perform survival analysis linking genomic features to clinical outcomes.
• Patient-centric queries: Patient-centered queries to inspect individual sample genomic profiles and associated data.
• Programmatic access: Programmatic data access via software interfaces for downstream computational analyses.

Scientific Applications:

• Integrative multi-omics analysis: Comparative and integrative analysis of genetic, epigenetic, transcriptomic, and proteomic data across cancer studies.
• Genotype–phenotype correlation: Correlation of genomic alterations with clinical attributes and outcomes to support translational research.
• Biomarker and prognostic discovery: Use of survival analysis and gene-level summaries to identify candidate biomarkers and prognostic signatures.
• Pathway and network analysis: Investigation of pathway alterations and network perturbations in cancer cohorts.
• Patient-specific genomic profiling: Examination of individual patient tumor profiles for research into personalized oncology.
• Computational pipeline integration: Programmatic retrieval of data for incorporation into downstream computational workflows and analyses.

Methodology:

Computational methods explicitly include generation of graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and programmatic access via software interfaces.