Mark D. Barnes

A Compendium of 49 Experimental SBS Signatures for Decoding Human Cancer Mutational Processes

The paper curates 49 experimental single-base substitution signatures from cancer genomes to link mutational processes to DNA damage mechanisms.

Assigning mutational signatures to individual samples and individual somatic mutations with SigProfilerAssignment

SigProfilerAssignment refits known substitution, doublet, indel and copy-number mutational signatures to single samples and probabilistically to individual mutations, outperforming four refitting tools on 2,700 synthetic genomes.

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

The paper introduces an updated tool for visualizing and exploring large mutational events in cancer genomes using two classification schemas.

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator

SigProfilerSimulator generates realistic null mutational landscapes for cancer genomics to evaluate bioinformatics tools and statistical analyses.

SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events

SigProfilerMatrixGenerator classifies and visualizes small mutational events in cancer genomes, offering faster and more comprehensive analysis than existing tools.