searchSubnet {signet} | R Documentation |
A simulated annealing algorithm to find the highest scoring subnetwork within a graph.
searchSubnet(pathway, scores, iterations = 1000, background)
pathway |
A gene network, or a list of gene networks,
in the |
scores |
A data frame with two columns: gene identifiers list (IDs have to be the same as for the pathways, e.g. Entrez) and associated scores. |
iterations |
Number of iterations. |
background |
For development purposes. |
A signet
object or a list of signet
objects. Each
signet
object consists in a table with gene IDs, their state,
their score; the subnetwork score and size and the p-value.
# Get KEGG pathways from the package graphite: # library(graphite) # kegg <- pathways("hsapiens", "kegg") # kegg_human <- lapply(kegg, pathwayGraph) data(daub13) # load the example gene scores #run the search in all the pathways with 2500 iterations (default) example <- searchSubnet(kegg_human, scores) summary(example)