import.genotypes

geno

Any 1 in "geno" will be interpreted as a an observed alteration labeled with type "event.type"

event.type

This is the color used for visualization of events labeled as of "event.type"

color


Import a matrix of 0/1 alterations as a TRONCO compliant dataset. Input "geno" can be either a dataframe or
a file name. In any case the dataframe or the table stored in the file must have a column for each altered
gene and a rows for each sample. Colnames will be used to determine gene names, if data is loaded from
file the first column will be assigned as rownames.



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

import.genotypes function

Import a matrix of 0/1 alterations as a TRONCO compliant dataset. Input "geno" can be either a dataframe or
a file name. In any case the dataframe or the table stored in the file must have a column for each altered
gene and a rows for each sample. Colnames will be used to determine gene names, if data is loaded from
file the first column will be assigned as rownames.

import.genotypes: import.genotypes

Description

Usage

Arguments

Value