recipe bioconductor-tronco

The TRONCO (TRanslational ONCOlogy) R package collects algorithms to infer progression models via the approach of Suppes-Bayes Causal Network, both from an ensemble of tumors (cross-sectional samples) and within an individual patient (multi-region or single-cell samples). The package provides parallel implementation of algorithms that process binary matrices where each row represents a tumor sample and each column a single-nucleotide or a structural variant driving the progression; a 0/1 value models the absence/presence of that alteration in the sample. The tool can import data from plain, MAF or GISTIC format files, and can fetch it from the cBioPortal for cancer genomics. Functions for data manipulation and visualization are provided, as well as functions to import/export such data to other bioinformatics tools for, e.g, clustering or detection of mutually exclusive alterations. Inferred models can be visualized and tested for their confidence via bootstrap and cross-validation. TRONCO is used for the implementation of the Pipeline for Cancer Inference (PICNIC).

Homepage

https://bioconductor.org/packages/3.9/bioc/html/TRONCO.html

License

file LICENSE

Recipe

/bioconductor-tronco/meta.yaml

package bioconductor-tronco

(downloads) docker_bioconductor-tronco

Versions

2.14.2-0

Depends bioconductor-rgraphviz

>=2.26.0,<2.27.0

Depends r-base

>=3.5.1,<3.5.2.0a0

Depends r-bnlearn

Depends r-cgdsr

Depends r-circlize

Depends r-doparallel

Depends r-foreach

Depends r-gridextra

Depends r-gtable

Depends r-gtools

Depends r-igraph

Depends r-iterators

Depends r-r.matlab

Depends r-rcolorbrewer

Depends r-scales

Depends r-xtable

Requirements

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-tronco

and update with:

conda update bioconductor-tronco

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-tronco:<tag>

(see bioconductor-tronco/tags for valid values for <tag>)