decompTumor2Sig

decompTumor2Sig decomposes individual tumor somatic mutation catalogs into predefined mutational signatures (Alexandrov-type and Shiraishi-type) to quantify the contributions of mutational processes underlying cancer genomes.

Key Features:

• Mutational signature decomposition: Decomposes individual tumor genomes' somatic mutation catalogs into predefined mutational signatures.
• Support for signature models: Implements both Alexandrov-type and Shiraishi-type signature models for analysis.
• Quantification of mutational processes: Estimates the contribution of each mutational signature to the observed somatic mutations in a tumor.

Scientific Applications:

• Cancer research: Identifies and quantifies mutational signatures to investigate mutational processes (e.g., cigarette smoke, age-related spontaneous deamination) and cancer etiology and progression.
• Personalized medicine: Decomposes individual tumor mutational landscapes to inform tailored analyses that can guide treatment-relevant interpretation.

Methodology:

Performs computational decomposition of somatic mutation catalogs using predefined Alexandrov-type and Shiraishi-type signatures, applies signatures defined from large tumor datasets, and has been validated on three test cases: 21 breast cancer genomes, 435 tumor genomes across ten tumor entities, and simulated tumor genomes.