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Related Experiment Video

Updated: Jan 20, 2026

Mycorrhizal Maps as a Tool to Explore Colonization Patterns and Fungal Strategies in the Roots of Festuca rubra and Zea mays
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SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events.

Erik N Bergstrom1, Mi Ni Huang2, Uma Mahto1

  • 1Department of Cellular and Molecular Medicine and Department of Bioengineering and Moores Cancer Center, University of California, San Diego, La Jolla, CA, 92093, USA.

BMC Genomics
|September 1, 2019
PubMed
Summary

SigProfilerMatrixGenerator is a new tool for classifying all small somatic mutational events in cancer genomes. It efficiently identifies mutational signatures, aiding in understanding cancer origins and evolution.

Keywords:
Mutational patternsMutational signaturesSomatic mutations

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Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Research

Background:

  • Cancer genomes contain somatic mutations from various mutational processes.
  • Understanding these mutational patterns helps identify cancer etiology.
  • Existing tools primarily focus on single base substitutions, lacking comprehensive classification of all small mutational events.

Purpose of the Study:

  • To introduce SigProfilerMatrixGenerator, a computational tool for classifying all types of small mutational events.
  • To provide a fast, accurate, and comprehensive method for analyzing mutational patterns.
  • To facilitate deeper understanding of mutational processes in cancer genomes.

Main Methods:

  • Developed SigProfilerMatrixGenerator, a Python-based tool with an R wrapper.
  • The tool generates fourteen distinct matrices by considering transcriptional strand bias.
  • It classifies single base substitutions, doublet base substitutions, and small insertions/deletions.

Main Results:

  • SigProfilerMatrixGenerator offers optimized exploration and visualization of mutational patterns.
  • It is faster and more memory-efficient than existing tools that generate single matrices.
  • The tool provides a comprehensive classification of mutations, including doublet substitutions and small indels.

Conclusions:

  • SigProfilerMatrixGenerator offers a standardized, efficient, and scalable method for classifying small mutational events.
  • It is the first tool to support classification of doublet base substitutions and small insertions/deletions alongside single base substitutions.
  • The tool is freely available with extensive documentation for broad accessibility.