Package: TRONCO
Version: 1.0.0
Date: 2014-09-22
Title: TRONCO, a package for TRanslational ONCOlogy
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@disco.unimib.it>,
 Alex Graudenzi <alex.graudenzi@disco.unimib.it>,
 Daniele Ramazzotti <daniele.ramazzotti@disco.unimib.it>
Depends: R (>= 2.10), methods, Rgraphviz, lattice, graph
Description: 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.
License: EPL (>= 1.0)
URL: http://bimib.disco.unimib.it
biocViews: Cancer
Suggests: RUnit, BiocGenerics
NeedsCompilation: no
Packaged: 2015-04-17 05:49:22 UTC; biocbuild
Built: R 3.2.0; ; 2015-04-17 14:01:43 UTC; windows
