Cargando…
MixClone: a mixture model for inferring tumor subclonal populations
BACKGROUND: Tumor genomes are often highly heterogeneous, consisting of genomes from multiple subclonal types. Complete characterization of all subclonal types is a fundamental need in tumor genome analysis. With the advancement of next-generation sequencing, computational methods have recently been...
Autores principales: | Li, Yi, Xie, Xiaohui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331709/ https://www.ncbi.nlm.nih.gov/pubmed/25707430 http://dx.doi.org/10.1186/1471-2164-16-S2-S1 |
Ejemplares similares
-
SeqClone: sequential Monte Carlo based inference of tumor subclones
por: Ogundijo, Oyetunji E., et al.
Publicado: (2019) -
A mixture model for expression deconvolution from RNA-seq in heterogeneous tissues
por: Li, Yi, et al.
Publicado: (2013) -
A mixture framework for inferring ancestral gene orders
por: Zhang, Yiwei, et al.
Publicado: (2012) -
PRISM: methylation pattern-based, reference-free inference of subclonal makeup
por: Lee, Dohoon, et al.
Publicado: (2019) -
Modeling and correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring
por: Chu, Yanshuo, et al.
Publicado: (2018)