Cargando…
Mutational signature learning with supervised negative binomial non-negative matrix factorization
MOTIVATION: Understanding the underlying mutational processes of cancer patients has been a long-standing goal in the community and promises to provide new insights that could improve cancer diagnoses and treatments. Mutational signatures are summaries of the mutational processes, and improving the...
Autores principales: | Lyu, Xinrui, Garret, Jean, Rätsch, Gunnar, Lehmann, Kjong-Van |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355241/ https://www.ncbi.nlm.nih.gov/pubmed/32657388 http://dx.doi.org/10.1093/bioinformatics/btaa473 |
Ejemplares similares
-
Identifying tumor clones in sparse single-cell mutation data
por: Myers, Matthew A, et al.
Publicado: (2020) -
Model selection and robust inference of mutational signatures using Negative Binomial non-negative matrix factorization
por: Pelizzola, Marta, et al.
Publicado: (2023) -
ClonArch: visualizing the spatial clonal architecture of tumors
por: Wu, Jiaqi, et al.
Publicado: (2020) -
Combinatorial and statistical prediction of gene expression from haplotype sequence
por: Alpay, Berk A, et al.
Publicado: (2020) -
REINDEER: efficient indexing of k-mer presence and abundance in sequencing datasets
por: Marchet, Camille, et al.
Publicado: (2020)