SparseSignatures: An R package using LASSO-regularized non-negative matrix factorization to identify mutational signatures from human tumor samples

Autor: Lorenzo Mella, Avantika Lal, Fabrizio Angaroni, Davide Maspero, Rocco Piazza, Arend Sidow, Marco Antoniotti, Alex Graudenzi, Daniele Ramazzotti
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: STAR Protocols, Vol 3, Iss 3, Pp 101513- (2022)
Druh dokumentu: article
ISSN: 2666-1667
DOI: 10.1016/j.xpro.2022.101513
Popis: Summary: We outline the features of the R package SparseSignatures and its application to determine the signatures contributing to mutation profiles of tumor samples. We describe installation details and illustrate a step-by-step approach to (1) prepare the data for signature analysis, (2) determine the optimal parameters, and (3) employ them to determine the signatures and related exposure levels in the point mutation dataset.For complete details on the use and execution of this protocol, please refer to Lal et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
Databáze: Directory of Open Access Journals