Cargando…
PyClone-VI: scalable inference of clonal population structures using whole genome data
BACKGROUND: At diagnosis tumours are typically composed of a mixture of genomically distinct malignant cell populations. Bulk sequencing of tumour samples coupled with computational deconvolution can be used to identify these populations and study cancer evolution. Existing computational methods for...
Autores principales: | Gillis, Sierra, Roth, Andrew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7730797/ https://www.ncbi.nlm.nih.gov/pubmed/33302872 http://dx.doi.org/10.1186/s12859-020-03919-2 |
Ejemplares similares
-
ddClone: joint statistical inference of clonal populations from single cell and bulk tumour sequencing data
por: Salehi, Sohrab, et al.
Publicado: (2017) -
A Novel Multi-Scale Modeling Approach to Infer Whole Genome Divergence
por: Reuveni, Eli, et al.
Publicado: (2012) -
PyGMQL: scalable data extraction and analysis for heterogeneous genomic datasets
por: Nanni, Luca, et al.
Publicado: (2019) -
Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies
por: WHEELER, NICHOLAS R., et al.
Publicado: (2020) -
TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data
por: Ha, Gavin, et al.
Publicado: (2014)