SASOM

SASOM identifies associations between cancer subtypes and sets of somatic mutations to detect subtype-associated genetic pathways.

Key Features:

• Association analysis: Tests associations between cancer subtypes and sets of somatic mutations to address low prevalence of individual mutations.
• Incorporation of functional information: Integrates functional annotations and pathway membership of mutations to improve biological interpretability.
• Robust statistical methodology (DAPC): Combines p-values across tests using the Distributed Analysis Procedure for Combining (DAPC) to synthesize evidence of association.
• Simulation studies: Validates performance with simulation experiments that assess type I error control and statistical power.
• Real-data application: Applied to cutaneous melanoma datasets to identify genetic pathways associated with immune-related subtypes.

Scientific Applications:

• Subtype association studies: Detects pathways and mutation sets associated with defined cancer subtypes using somatic mutation data.
• Functional interpretation of somatic mutations: Prioritizes biologically relevant mutations by leveraging pathway and functional information.
• Subtype-specific biological characterization: Supports analyses linking mutation patterns to subtype-specific biology, including immune-related subtypes.

Methodology:

Performs set-based association testing between somatic mutation sets (often pathway-derived) and cancer subtypes, integrates functional mutation annotations, combines significance measures using DAPC, and is validated by simulation studies assessing type I error and power.