mutalisk

mutalisk analyzes somatic mutations to correlate mutation patterns with genomic, transcriptional, and epigenomic contexts and to decompose mutations into mutational signatures for studying mutational processes in cancer.

Key Features:

• Correlation with Genomic Contexts: Integrates somatic mutations with DNA sequence contexts, replication dynamics, RNA transcription activities, and epigenomic chromatin organization to assess the influence of local genomic environment on mutation rates.
• Identification of Hypermutations: Detects localized hypermutation events (kataegis) characterized by clusters of mutations in specific genomic regions.
• Decomposition into Mutational Signatures: Dissects somatic mutations into constituent mutational signatures using maximum likelihood estimation to identify and quantify known mutational signatures.
• Association with Regulatory Elements: Assesses relationships between mutation density and regulatory elements to elucidate impacts on gene regulation and genomic instability.

Scientific Applications:

• Oncology research: Analyzes the diversity and evolution of mutational processes in cancer genomes.
• Mutagenic factor inference: Provides insights into mutagenic factors influencing somatic mutations.
• Clonal evolution and therapeutics: Aids study of clonal evolution in cancer cells and informs therapeutic strategy investigations.

Methodology:

Integrates genomic, transcriptional, and epigenomic data to correlate somatic mutations with biological features, detects kataegis clusters, and uses maximum likelihood estimation to decompose mutation spectra into mutational signatures.