integrative somatic mutation analysis (isma)

integrative somatic mutation analysis (isma) integrates somatic mutation calls from multiple pipelines applied to matched tumor–normal next-generation sequencing data to produce unified mutation catalogues and quantify consensus, variability, and outliers for cancer genomic analysis.

Key Features:

• R package: Implemented as an R package for programmatic analysis of somatic mutation call sets.
• Integration of multiple pipelines: Integrates results from various somatic mutation detection tools applied to matched tumor–normal samples to reconcile discrepancies between pipelines.
• Quantification and analysis: Quantifies consensus levels among detected mutations, estimates variability, identifies outliers, and integrates evidence from publicly available mutation catalogues.
• Filtering strategies: Supports design and application of filtering strategies to identify high-confidence somatic mutation sites leveraging data from The Cancer Genome Atlas (TCGA).
• Report generation: Produces detailed outputs highlighting common patterns, variability, and previously catalogued sites across cancer types such as breast cancer.

Scientific Applications:

• Oncology research: Improves robustness of somatic mutation detection for studies of tumor biology and identification of clinically relevant genetic alterations for targeted therapies.
• Pipeline benchmarking: Enables comparative evaluation of somatic mutation detection pipelines by assessing consensus and variability among call sets.
• Mutation catalogue curation: Integrates pipeline-derived calls with public catalogues such as TCGA to refine unified mutation catalogues for cancer-specific analyses, including breast cancer.

Methodology:

Performs systematic comparison of somatic mutation data from different computational tools, processes these data to generate a unified mutation catalogue, and analyzes the catalogue to identify consensus mutations and assess variability.