In caravagnalab/mobster: MOBSTER - Model-based tumour subclonal deconvolution

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

mobster

mobster is a package that implements a model-based approach for subclonal deconvolution of cancer genome sequencing data (Caravagna et al; PMID: 32879509).

The package integrates evolutionary theory (i.e., population) and Machine-Learning to analyze (e.g., whole-genome) bulk data from cancer samples. This analysis relates to clustering; we approach it via a maximum-likelihood formulation of Dirichlet mixture models, and use bootstrap routines to assess the confidence of the parameters. The package implements S3 objects to visualize the data and the fits.

Citation

If you use mobster, please cite:

• G. Caravagna, T. Heide, M.J. Williams, L. Zapata, D. Nichol, K. Chkhaidze, W. Cross, G.D. Cresswell, B. Werner, A. Acar, L. Chesler, C.P. Barnes, G. Sanguinetti, T.A. Graham, A. Sottoriva. Subclonal reconstruction of tumors by using machine learning and population genetics. Nature Genetics 52, 898–907 (2020).

Help and support

Installation

You can install the released version of mobster from GitHub with:

# install.packages("devtools")
devtools::install_github("caravagnalab/mobster")

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Copyright and contacts

Giulio Caravagna. Cancer Data Science (CDS) Laboratory.

caravagnalab/mobster documentation built on March 25, 2023, 3:40 p.m.