mutSigMapper

mutSigMapper implements a shot-noise-based model in R to generate spectral ensembles and map observed mutational spectra to mutational signatures while prioritizing parsimonious and biologically plausible exposures.

Key Features:

• Shot-Noise Modeling: Implements a shot-noise framework to simulate spectral ensembles that reflect the stochastic nature of mutation occurrences.
• Parsimonious and Biologically Plausible Exposures: Identifies parsimonious exposure solutions and favors biologically plausible explanations when mapping signatures to spectra.
• Quantitative and Non-Parametric Assessment: Provides a quantitative, non-parametric framework to assess statistical significance of signature exposures without relying on parametric assumptions.

Scientific Applications:

• Cancer Genomics: Maps mutational signatures to exposures and biological processes to investigate mutational etiologies, inform treatment strategies, support prognostic assessments, and help identify therapeutic targets for personalized medicine.

Methodology:

Generates spectral ensembles via a shot-noise model to simulate stochastic mutation occurrences and compares simulated spectra with observed spectra to identify significant mutational signatures.