Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator

BACKGROUND: Performing a statistical test requires a null hypothesis. In cancer genomics, a key challenge is the fast generation of accurate somatic mutational landscapes that can be used as a realistic null hypothesis for making biological discoveries. RESULTS: Here we present SigProfilerSimulator,...

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Detalles Bibliográficos
Autores principales: Bergstrom, Erik N., Barnes, Mark, Martincorena, Iñigo, Alexandrov, Ludmil B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539472/
https://www.ncbi.nlm.nih.gov/pubmed/33028213
http://dx.doi.org/10.1186/s12859-020-03772-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539472/
https://www.ncbi.nlm.nih.gov/pubmed/33028213
http://dx.doi.org/10.1186/s12859-020-03772-3

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