plotPaths: Plots an annotated igraph object higlighting ranked paths.

In ahmohamed/NetPathMiner: NetPathMiner for Biological Network Construction, Path Mining and Visualization

Plots an annotated igraph object higlighting ranked paths.

Description

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

Usage

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

	## 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)

ahmohamed/NetPathMiner documentation built on Nov. 30, 2024, 1:18 a.m.