Convert a ranked path list to Edge ids of a graph, where paths can come from a different representation (for example matching path from a reaction network to edges on a metabolic network).
getPathsAsEIDs(paths, graph)The paths extracted by pathRanker.
A annotated igraph object.
A list of edge ids on the provided graph.
Other Path ranking methods:
extractPathNetwork(),
pathRanker()
## 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)
#> This graph was created by an old(er) igraph version.
#> ℹ Call `igraph::upgrade_graph()` on it to use with the current igraph version.
#> For now we convert it on the fly...
## 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)
#> 100 genes were present in the microarray, but not represented in the network.
#> 55 genes were couldn't be found in microarray.
#> Assigning edge weights for label ALL1/AF4
#> Assigning edge weights for label BCR/ABL
#> Assigning edge weights for label E2A/PBX1
#> Assigning edge weights for label NEG
## Get ranked paths using probabilistic shortest paths.
ranked.p <- pathRanker(rgraph, method="prob.shortest.path",
K=20, minPathSize=6)
#> Extracting the 20 most probable paths for ALL1/AF4
#> Extracting the 20 most probable paths for BCR/ABL
#> Extracting the 20 most probable paths for E2A/PBX1
#> Extracting the 20 most probable paths for NEG
## Get the edge ids along paths in the reaction graph.
path.eids <- getPathsAsEIDs(ranked.p, rgraph)
## Get the edge ids along paths in the original metabolic graph.
path.eids <- getPathsAsEIDs(ranked.p, ex_sbml)