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title: 'RESOLVE: RESOLVE: An R package for the efficient analysis of mutational signatures
  from cancer genomes'
version: 1.7.0
abstract: Cancer is a genetic disease caused by somatic mutations in genes controlling
  key biological functions such as cellular growth and division. Such mutations may
  arise both through cell-intrinsic and exogenous processes, generating characteristic
  mutational patterns over the genome named mutational signatures. The study of mutational
  signatures have become a standard component of modern genomics studies, since it
  can reveal which (environmental and endogenous) mutagenic processes are active in
  a tumor, and may highlight markers for therapeutic response. Mutational signatures
  computational analysis presents many pitfalls. First, the task of determining the
  number of signatures is very complex and depends on heuristics. Second, several
  signatures have no clear etiology, casting doubt on them being computational artifacts
  rather than due to mutagenic processes. Last, approaches for signatures assignment
  are greatly influenced by the set of signatures used for the analysis. To overcome
  these limitations, we developed RESOLVE (Robust EStimation Of mutationaL signatures
  Via rEgularization), a framework that allows the efficient extraction and assignment
  of mutational signatures. RESOLVE implements a novel algorithm that enables (i)
  the efficient extraction, (ii) exposure estimation, and (iii) confidence assessment
  during the computational inference of mutational signatures.
authors:
- family-names: Ramazzotti
  given-names: Daniele
  email: daniele.ramazzotti@unimib.it
  orcid: https://orcid.org/0000-0002-6087-2666
- family-names: De Sano
  given-names: Luca
  email: luca.desano@gmail.com
  orcid: https://orcid.org/0000-0002-9618-3774
repository: https://bioc.r-universe.dev
repository-code: https://github.com/danro9685/RESOLVE
url: https://github.com/danro9685/RESOLVE
date-released: '2024-03-21'
contact:
- family-names: De Sano
  given-names: Luca
  email: luca.desano@gmail.com
  orcid: https://orcid.org/0000-0002-9618-3774