SigProfiler (original) (raw)

Framework for Deciphering Mutational Signatures from Mutational Catalogues of Cancer Genomes

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Aktualisiert13. Dez 2020

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IMPORTANT: MATLAB version of SigProfiler will not be updated or supported in the future. Completely redesigned and much better performing Python tool, named, SigProfilerExtractor, for extracting mutational signatures is now available at: https://github.com/AlexandrovLab/SigProfilerExtractor

The genome of a cancer cell carries somatic mutations that are the cumulative consequence of the DNA damage and repair processes. Until now there have been no theoretical models describing the signatures of mutational processes operative in cancer genomes and no systematic computational approaches are available to decipher these mutational signatures. Here, we introduce a MATLAB based computational framework that effectively addresses these questions. Our approach provides a basis for characterizing mutational signatures from cancer-derived somatic mutational catalogues, paving the way to insights into the common pathogenetic mechanism underlying all cancers. Please see the included readme.pdf file and the supporting articles for more information about the theoretical model and how to use the provided computational framework.

Zitieren als

Ludmil Alexandrov (2025). SigProfiler (https://www.mathworks.com/matlabcentral/fileexchange/38724-sigprofiler), MATLAB Central File Exchange. Abgerufen2. Mai 2025.

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Erstellt mit R2017b

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