Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

• DOI: 10.1101/2023.02.03.527015
• Publication Date: 2023-02-05T05:35:14Z
• Authors: Azhar Khandekar; Raviteja Vangara; Mark Barnes; Marcos Díaz-Gay; Ammal Abbasi; Erik N. Bergstrom; Christopher D. St...; Nischalan Pillay; Ludmil B. Alexandrov
• Keywords: Python

All cancers harbor somatic mutations in their genomes. In principle, affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large events affect more than pairs, and, most cases, they encompass copy-number structural variants many thousands of pairs. Prior studies have demonstrated that examining patterns can be leveraged to provide both biological clinical insights, thus, resulting an extensive repertoire tools for evaluating Recently, classification schemas large-scale emerged shown utility across the spectrum human cancers. However, there has been no standard bioinformatics tool allows visualizing exploring these events.Here, we present a new version SigProfilerMatrixGenerator now delivers integrated capabilities The provides support under two previously developed it supports data from numerous algorithms modalities. is written Python with R wrapper package provided users prefer working environment.The first standardized optimized exploration visualization copy number variants. freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator documentation https://osf.io/s93d5/wiki/home/ .