plotAllNetworks: Higlighting ranked paths over multiple network...

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

Higlighting ranked paths over multiple network representations.

Description

This function highlighting ranked paths over different network representations, metabolic, reaction and gene networks. The functions finds equivalent paths across different networks and marks them.

Usage

plotAllNetworks(
  paths,
  metabolic.net = NULL,
  reaction.net = NULL,
  gene.net = NULL,
  path.clusters = NULL,
  plot.clusters = TRUE,
  col.palette = palette(),
  layout = layout.auto,
  ...
)

Arguments

paths	The result of pathRanker.
metabolic.net	A bipartite metabolic network.
reaction.net	A reaction network, resulting from makeReactionNetwork.
gene.net	A gene network, resulting from makeGeneNetwork.
path.clusters	The result from pathCluster or pathClassifier.
plot.clusters	Whether to plot clustering information, as generated by plotClusters
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

Highlights the path list over all provided networks.

Author(s)

Ahmed Mohamed

See Also

Other Plotting methods: colorVertexByAttr(), layoutVertexByAttr(), plotClassifierROC(), plotClusterMatrix(), plotCytoscapeGML(), plotNetwork(), plotPathClassifier(), plotPaths()

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)

plotAllNetworks(ranked.p, metabolic.net = ex_sbml, reaction.net = rgraph,
					vertex.label = "", vertex.size = 4)

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