TRONCO

This package is for version 3.1 of Bioconductor; for the stable, up-to-date release version, see TRONCO.

TRONCO, a package for TRanslational ONCOlogy

Bioconductor version: 3.1

Genotype-level cancer progression models describe the ordering of accumulating mutations, e.g., somatic mutations / copy number variations, during cancer development. These graphical models help understand the causal structure involving events promoting cancer progression, possibly predicting complex patterns characterising genomic progression of a cancer. Reconstructed models can be used to better characterise genotype-phenotype relation, and suggest novel targets for therapy design. TRONCO (TRanslational ONCOlogy) is a R package aimed at collecting state-of-the-art algorithms to infer progression models from cross-sectional data, i.e., data collected from independent patients which does not necessarily incorporate any evident temporal information. These algorithms require a binary input matrix where: (i) each row represents a patient genome, (ii) each column an event relevant to the progression (a priori selected) and a 0/1 value models the absence/presence of a certain mutation in a certain patient. The current first version of TRONCO implements the CAPRESE algorithm (Cancer PRogression Extraction with Single Edges) to infer possible progression models arranged as trees; cfr. Inferring tree causal models of cancer progression with probability raising, L. Olde Loohuis, G. Caravagna, A. Graudenzi, D. Ramazzotti, G. Mauri, M. Antoniotti and B. Mishra. PLoS One, to appear. This vignette shows how to use TRONCO to infer a tree model of ovarian cancer progression from CGH data of copy number alterations (classified as gains or losses over chromosome's arms). The dataset used is available in the SKY/M-FISH database.

Author: Marco Antoniotti, Giulio Caravagna, Alex Graudenzi, Ilya Korsunsky, Mattia Longoni, Loes Olde Loohuis, Giancarlo Mauri, Bud Mishra, Daniele Ramazzotti

Maintainer: Giulio Caravagna <giulio.caravagna at disco.unimib.it>, Alex Graudenzi <alex.graudenzi at disco.unimib.it>, Daniele Ramazzotti <daniele.ramazzotti at disco.unimib.it>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("TRONCO")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("TRONCO")

Details

Package Archives

Follow Installation instructions to use this package in your R session.