Description Usage Arguments Value Author(s) See Also Examples
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.
1 2 3 |
paths |
The result of |
metabolic.net |
A bipartite metabolic network. |
reaction.net |
A reaction network, resulting from |
gene.net |
A gene network, resulting from |
path.clusters |
The result from |
plot.clusters |
Whether to plot clustering information, as generated by |
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 |
Highlights the path list over all provided networks.
Ahmed Mohamed
Other Plotting methods: colorVertexByAttr
,
layoutVertexByAttr
,
plotClassifierROC
,
plotClusterMatrix
,
plotCytoscapeGML
,
plotNetwork
,
plotPathClassifier
, plotPaths
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## 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)
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