Sigflow

Sigflow performs mutational signature analysis of cancer genomic alterations to extract, fit, and evaluate mutational signatures for studies of mutational processes.

Key Features:

• De novo Signature Extraction: Performs de novo extraction of mutational signatures directly from genomic data.
• Reference Signature Fitting: Fits mutation data to all or specified COSMIC reference signatures, including single base substitution (SBS), doublet base substitution (DBS), small insertion and deletion (INDEL), and copy number alterations.
• Signature Stability Analysis: Uses bootstrapping to assess the stability and reproducibility of identified mutational signatures.
• Sample Clustering: Clusters samples based on signature exposures across multiple types of genomic alterations.
• Reproducibility and Environment Control: Distributed as a Docker image to version-control dependent tools and computational environments for reproducible analyses.
• Cross-Species Application: Applicable to both human and mouse genomes.

Scientific Applications:

• Mutational Landscape Analysis: Characterizes mutational processes shaping cancer genomes.
• Cancer Stratification: Enables stratification of cancer cases by signature exposure profiles.
• Biomarker and Target Discovery: Supports identification of potential therapeutic targets and biomarkers based on mutational signatures.
• Comparative Genomics: Facilitates comparative analyses across human and mouse genomic data.

Methodology:

Performs data preprocessing, de novo signature extraction, fitting to COSMIC reference signatures (SBS, DBS, INDEL, copy number), bootstrapping-based stability analysis, and clustering of samples by signature exposure.