plotPaths: Plots an annotated igraph object higlighting ranked paths.

Description Usage Arguments Value Author(s) See Also Examples

View source: R/plotPath.R

Description

This function plots a network highlighting ranked paths. If path.clusters are provided, paths in the same cluster are assigned similar colors.

Usage

1
2
plotPaths(paths, graph, path.clusters = NULL, col.palette = palette(),
  layout = layout.auto, ...)

Arguments

paths

The result of pathRanker.

graph

An annotated igraph object.

path.clusters

The result from pathCluster or pathClassifier.

col.palette

A color palette, or a palette generating function (ex:

col.palette=rainbow

).

layout

Either a graph layout function, or a two-column matrix specifiying vertex coordinates.

...

Additional arguments passed to plotNetwork.

Value

Produces a plot of the network with paths highlighted. If paths are computed for several labels (sample categories), a plot is created for each label.

Author(s)

Ahmed Mohamed

See Also

Other Plotting methods: colorVertexByAttr, layoutVertexByAttr, plotAllNetworks, plotClassifierROC, plotClusterMatrix, plotCytoscapeGML, plotNetwork, plotPathClassifier

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
	## Prepare a weighted reaction network.
	## Conver a metabolic network to a reaction network.
 data(ex_sbml) # bipartite metabolic network of Carbohydrate metabolism.
 rgraph <- makeReactionNetwork(ex_sbml, simplify=TRUE)

	## Assign edge weights based on Affymetrix attributes and microarray dataset.
 # Calculate Pearson's correlation.
	data(ex_microarray)	# Part of ALL dataset.
	rgraph <- assignEdgeWeights(microarray = ex_microarray, graph = rgraph,
		weight.method = "cor", use.attr="miriam.uniprot",
		y=factor(colnames(ex_microarray)), bootstrap = FALSE)

	## Get ranked paths using probabilistic shortest paths.
 ranked.p <- pathRanker(rgraph, method="prob.shortest.path",
					K=20, minPathSize=6)

	## Plot paths.
	plotPaths(ranked.p, rgraph)

	## Convert paths to binary matrix, build a classifier.
	ybinpaths <- pathsToBinary(ranked.p)
	p.class <- pathClassifier(ybinpaths, target.class = "BCR/ABL", M = 3)

 ## Plotting with clusters, on a metabolic graph.
	plotPaths(ranked.p, ex_sbml, path.clusters=p.class)

NetPathMiner documentation built on Nov. 8, 2020, 8:20 p.m.