Methods for reconstructing tumor evolution are benchmarked in the DREAM Somatic Mutation Calling Tumour Heterogeneity Challenge. Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogeneity to infer evolutionary dynamics. A growing number of studies have used these approaches to link cancer evolution with clinical progression and response to therapy. Although the inference of tumor phylogenies is rapidly becoming standard practice in cancer genome analyses, standards for evaluating them are lacking. To address this need, we systematically assess methods for reconstructing tumor subclonality. First, we elucidate the main algorithmic problems in subclonal reconstruction and develop quantitative metr...
BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structur...
<div><p>Recent improvements in next-generation sequencing of tumor samples and the ability to identi...
As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding ...
Methods for reconstructing tumor evolution are benchmarked in the DREAM Somatic Mutation Calling Tum...
Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogen...
Thesis advisor: Gabor MarthUnlike normal tissue cells, which contain identical copies of the same ge...
Tumours accumulate many somatic mutations in their lifetime. Some of these mutations, drivers, conve...
Tumours are composed of multiple subpopulations, each of which has its own genotype and phenotype. ...
Accelerating technological advances have allowed the widespread genomic profiling of tumors. As yet,...
Clonal evolution model of cancer provides a conceptual framework to interpret spatial and temporal i...
Abstract Background The phenotypes of cancer cells ar...
SummaryThe extensive genetic heterogeneity of cancers can greatly affect therapy success due to the ...
Background: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencin...
A comprehensive understanding of the clonal evolution of cancer is critical for understanding neopla...
Whole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumo...
BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structur...
<div><p>Recent improvements in next-generation sequencing of tumor samples and the ability to identi...
As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding ...
Methods for reconstructing tumor evolution are benchmarked in the DREAM Somatic Mutation Calling Tum...
Tumor DNA sequencing data can be interpreted by computational methods that analyze genomic heterogen...
Thesis advisor: Gabor MarthUnlike normal tissue cells, which contain identical copies of the same ge...
Tumours accumulate many somatic mutations in their lifetime. Some of these mutations, drivers, conve...
Tumours are composed of multiple subpopulations, each of which has its own genotype and phenotype. ...
Accelerating technological advances have allowed the widespread genomic profiling of tumors. As yet,...
Clonal evolution model of cancer provides a conceptual framework to interpret spatial and temporal i...
Abstract Background The phenotypes of cancer cells ar...
SummaryThe extensive genetic heterogeneity of cancers can greatly affect therapy success due to the ...
Background: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencin...
A comprehensive understanding of the clonal evolution of cancer is critical for understanding neopla...
Whole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumo...
BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structur...
<div><p>Recent improvements in next-generation sequencing of tumor samples and the ability to identi...
As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding ...