hypothesis.add.group

Type of pattern to be added, e.g., co-occurance, soft or hard exclusivity.

group

pattern.cause

pattern.effect

Minimum cardinality of the subgroups to be considered.

dim.min

Maximum cardinality of the subgroups to be considered.

dim.max

Minimum probability associated to each valid group.

min.prob

A parameter to disable/enable verbose messages.

silent


Add all the hypotheses related to a group of events



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.

Giulio Caravagna 
Alex Graudenzi alexgraudenzidiscounimibit
Daniele Ramazzotti danieleramazzottidiscounimibit

TRONCO


An R package for the inference of cancer progression models from heterogeneous genomic data

TRONCO, an R package for TRanslational ONCOlogy

hypothesis.add.group function

Add all the hypotheses related to a group of events

hypothesis.add.group: hypothesis add group

Description

Usage

Arguments

Value