Paper Info
Title
The Mobster R Package For Tumour Subclonal Deconvolution From Bulk Dna Whole-Genome Sequencing Data
Abstract
BackgroundThe large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories.ResultsIn a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution.ConclusionsWe present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities.
Year
DOI
Venue
2020
10.1186/s12859-020-03863-1
BMC BIOINFORMATICS
Keywords
DocType
Volume
Tumour subclonal deconvolution, Cancer evolution, Population genetics, Dirichlet mixture model, Whole-genome DNA sequencing
Journal
21
Issue
ISSN
Citations 
1
1471-2105
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Giulio Caravagna115616.46
Guido Sanguinetti277257.09
Trevor A Graham310.69
Andrea Sottoriva471.87