FABRIC Cancer Portal

FABRIC Cancer Portal catalogs selection signals on human protein-coding genes across tumors to quantify gene-level selection and evaluate potential cancer driver roles.

Key Features:

• Coverage: Analyzes approximately 18,000 protein-coding genes across 33 distinct cancer types and pan-cancer cohorts.
• Gene selection quantification: Quantifies gene-level selection across tumors and evaluates potential roles of genes as cancer drivers.
• Statistical ranking: Applies a robust statistical methodology to rank genes by the strength of evidence for selection in tumors.
• Annotation integration: Leverages a combination of genomic and proteomic annotations and integrates proteomic data with genomic insights.
• Framework: Developed and implemented within the FABRIC framework.
• Cross-references: Provides curated cross-references to other genomic, proteomic, and cancer-related resources.

Scientific Applications:

• Cancer driver identification: Prioritizes known and candidate cancer driver genes based on selection evidence.
• Comparative cancer-type analysis: Compares gene selection signals across multiple cancer types and in pan-cancer analyses.
• Molecular interpretation: Uses integrated genomic and proteomic annotations to support molecular interpretation of selection signals.
• Integrative studies: Facilitates integrative analyses by linking gene-level selection results with external genomic and proteomic datasets.

Methodology:

Within the FABRIC framework, a statistical methodology quantifies gene-level selection and ranks genes by evidence for selection across tumors using genomic and proteomic annotations across ~18,000 protein-coding genes in 33 cancer types and pan-cancer analyses.