Cargando…
Characterization of tumor heterogeneity by latent haplotypes: a sequential Monte Carlo approach
Tumor samples obtained from a single cancer patient spatially or temporally often consist of varying cell populations, each harboring distinct mutations that uniquely characterize its genome. Thus, in any given samples of a tumor having more than two haplotypes, defined as a scaffold of single nucle...
Autores principales: | Ogundijo, Oyetunji E., Wang, Xiaodong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984585/ https://www.ncbi.nlm.nih.gov/pubmed/29868266 http://dx.doi.org/10.7717/peerj.4838 |
Ejemplares similares
-
A sequential Monte Carlo approach to gene expression deconvolution
por: Ogundijo, Oyetunji E., et al.
Publicado: (2017) -
SeqClone: sequential Monte Carlo based inference of tumor subclones
por: Ogundijo, Oyetunji E., et al.
Publicado: (2019) -
Bayesian estimation of scaled mutation rate under the coalescent: a sequential Monte Carlo approach
por: Ogundijo, Oyetunji E., et al.
Publicado: (2017) -
A sequential Monte Carlo algorithm for inference of subclonal structure in cancer
por: Ogundijo, Oyetunji E., et al.
Publicado: (2019) -
A sequential Monte Carlo framework for haplotype inference in CNV/SNP genotype data
por: Iliadis, Alexandros, et al.
Publicado: (2014)