Test the significance of high-scoring subnetworks found using simulated annealing.
A list of signet objects obtained using the
Vector of null subnetwork scores generated using the
signet object, a p-value is computed given the
provided emnpirical null distribution.
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# Get KEGG pathways from the package graphite: # library(graphite) # kegg <- pathways("hsapiens", "kegg") # kegg_human <- lapply(kegg, pathwayGraph) data(daub13) # load the gene scores from Daub et al. (2013) #run the search in all the pathways with 2500 iterations (default) example <- searchSubnet(kegg_human, scores) # generate the null distribution (here, only 5 values, but # at least 1000 are advised) null <- nullDist(kegg_human, scores, n = 5) example <- testSubnet(example, null) #now, 'example' includes p-values summary(example)
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