searchSubnet: Search for a high scoring subnetwork

In signet: signet: Selection Inference in Gene NETworks

Description

A simulated annealing algorithm to find the highest scoring subnetwork within a graph.

Usage

searchSubnet(pathway, scores, iterations = 1000, background)

Arguments

pathway	A gene network, or a list of gene networks, in the graphNEL format.
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.

Value

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.

Examples

# 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)

signet documentation built on April 28, 2020, 7:54 p.m.