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Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment
Marcos Díaz-Gay1,2,3, Raviteja Vangara1,2,3, Mark Barnes1,2,3
1Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, 92093, USA.
Biorxiv : the Preprint Server for Biology
|July 28, 2023
Summary
SigProfilerAssignment accurately assigns mutational signatures, including copy-number variations, to cancer genomes. This computational tool enhances understanding of cancer evolution by identifying mutagenic processes.
Area of Science:
- Genomics and Computational Biology
- Cancer Research and Mutagenesis
Background:
- Understanding cancer genome evolution relies on analyzing mutational signatures.
- Accurate assignment of these signatures to individual samples is crucial for research.
Approach:
- Introduced SigProfilerAssignment, a computational framework for assigning mutational signatures.
- This tool uniquely enables analysis of copy-number signatures and probabilistic assignment to somatic mutations.
- Utilizes a custom implementation of the forward stagewise algorithm and nonnegative least squares for optimization.
Key Points:
- SigProfilerAssignment is the first tool to analyze copy-number signatures and assign signatures to individual somatic mutations.
- Demonstrated superior performance over four common approaches using 2,700 synthetic cancer genomes.
- Provides both desktop and online implementations for accessibility.
Conclusions:
- SigProfilerAssignment offers a robust method for assigning mutational signatures in cancer genomics.
- The framework advances the study of mutagenic processes and cancer genome evolution.
- Freely available for research use.
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