Cargando…
THetA: inferring intra-tumor heterogeneity from high-throughput DNA sequencing data
Tumor samples are typically heterogeneous, containing admixture by normal, non-cancerous cells and one or more subpopulations of cancerous cells. Whole-genome sequencing of a tumor sample yields reads from this mixture, but does not directly reveal the cell of origin for each read. We introduce THet...
Autores principales: | Oesper, Layla, Mahmoody, Ahmad, Raphael, Benjamin J |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4054893/ https://www.ncbi.nlm.nih.gov/pubmed/23895164 http://dx.doi.org/10.1186/gb-2013-14-7-r80 |
Ejemplares similares
-
A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data
por: Hajirasouliha, Iman, et al.
Publicado: (2014) -
Parameter, noise, and tree topology effects in tumor phylogeny inference
por: Tomlinson, Kiran, et al.
Publicado: (2019) -
Reconstruction of clonal trees and tumor composition from multi-sample sequencing data
por: El-Kebir, Mohammed, et al.
Publicado: (2015) -
High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics
por: Pellegrino, Maurizio, et al.
Publicado: (2018) -
FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing
por: Shen, Ronglai, et al.
Publicado: (2016)