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Giulio Caravagna edited this page Dec 4, 2018 · 25 revisions

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REVOLVER is a tool for Transfer Learning (TL) in Cancer Evolution.

TL is a relatively new declination of Machine Learning in which we share information across learning tasks and domains to increase our performance. TL is an umbrella term for several paradigms; in REVOLVER what we do is actually Multi-task Learning.

REVOLVER correlates the task of selecting n trees from n patients for which sequencing data from one or more samples is available. The method, its mathematical ground and the pseudocode of the algorithm are described in the main paper.

  • G. Caravagna, Y. Giarratano, D. Ramazzoti, I. Tomlinson, T.A. Graham, G. Sanguinetti, A. Sottoriva. Detecting repeated cancer evolution from multi-region tumor sequencing data. Nature Methods 15, 707–714 (2018).

For question about the tool and the analysis of your data, please look at the open and closed issues. You might also want to look at the FAQ.

Current version: released ~June 2018, codename "Haggis and tatties"

News: see README

Author: Giulio Caravagna , Institute of Cancer Research, UK.

Contact: [@gcaravagna; [email protected]]

Installation

# Required external packages available on CRAN: 
# "cluster", "crayon", "dendextend", "dynamicTreeCut", 
# "doParallel", "foreach", "igraph", "parallel"

# Required external packages available on GitHub: "caravagn/pio"

devtools::install_github("caravagn/revolver")
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