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TRONCO (version 2.4.2)

tronco.plot: tronco.plot

Description

Plots a progression model from a recostructed dataset

Usage

tronco.plot(x, models = names(x$model), fontsize = NA, height = 2, width = 3, height.logic = 1, pf = FALSE, disconnected = FALSE, scale.nodes = NA, title = as.description(x), confidence = NA, p.min = 0.05, legend = TRUE, legend.cex = 1, edge.cex = 1, label.edge.size = NA, expand = TRUE, genes = NULL, relations.filter = NA, edge.color = "black", pathways.color = "Set1", file = NA, legend.pos = "bottom", pathways = NULL, lwd = 3, samples.annotation = NA, export.igraph = FALSE, ...)

Arguments

x
A reconstructed model (the output of the inference by a tronco function)
models
A vector containing the names of the algorithms used (caprese, capri_bic, etc)
fontsize
For node names. Default NA for automatic rescaling
height
Proportion node height - node width. Default height 2
width
Proportion node height - node width. Default width 2
height.logic
Height of logical nodes. Defaul 1
pf
Should I print Prima Facie? Default False
disconnected
Should I print disconnected nodes? Default False
scale.nodes
Node scaling coefficient (based on node frequency). Default NA (autoscale)
title
Title of the plot. Default as.description(x)
confidence
Should I add confidence informations? No if NA
p.min
p-value cutoff. Default automatic
legend
Should I visualise the legend?
legend.cex
CEX value for legend. Default 1.0
edge.cex
CEX value for edge labels. Default 1.0
label.edge.size
Size of edge labels. Default NA for automatic rescaling
expand
Should I expand hypotheses? Default TRUE
genes
Visualise only genes in this list. Default NULL, visualise all.
relations.filter
Filter relations to dispaly according to this functions. Default NA
edge.color
Edge color. Default 'black'
pathways.color
RColorBrewer colorser for patways. Default 'Set1'.
file
String containing filename for PDF output. If NA no PDF output will be provided
legend.pos
Legend position. Default 'bottom',
pathways
A vector containing pathways information as described in as.patterns()
lwd
Edge base lwd. Default 3
samples.annotation
= List of samples to search for events in model
export.igraph
If TRUE export the igraph object generated
...
Additional arguments for RGraphviz plot function

Value

Information about the reconstructed model

Examples

Run this code
data(test_model)
tronco.plot(test_model)

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