Function to write an input file with the node scores for HEINZ. This file is used
together with the edge input file to calculate the maximum scoring subnetwork of the
graph. The scores are matched by their names to the nodes of the network, therefore if
nodes.scores are provided as a vector or matrix, the vector has to be named, respectively the matrix has to be provided
If the network contains more nodes than the score vector, the nodes without a score are scored
with the average over all nodes. If the nodes should not be scored and used for the calculation of the
maximum scoring subnetwork, draw a subnetwork
subNetwork first and use this for the argument network.
Network from which to calculate the maximum scoring subnetwork.
File to write to.
Numeric vector or matrix of scores for the nodes of the network. Names of the vector or rownames of the matrix have to correspond to the PPI identifiers of the network. The scores can also be used from the node attribute "score", given one score for each node.
Boolean value, whether to use the node attribute "score" in the network as node scores.
scoreFunctionto derive scores from a vector of p-values.
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#create small network library(DLBCL) data(interactome) small.net <- subNetwork(nodes(interactome)[0:15], interactome) scores <- c(1:length(nodes(small.net))) names(scores) <- nodes(small.net) ## Not run: writeHeinzNodes(network=small.net, file="test_nodes", node.scores=scores) # use Lymphoma data and graph to find module library(DLBCL) data(interactome) data(dataLym) # get induced subnetwork for all genes contained on the chip chipGraph <- subNetwork(dataLym$label, interactome) ## Not run: writeHeinzEdges(network=chipGraph, file="lymphoma_edges_001", use.score=FALSE) score <- dataLym$score001 names(score) <- dataLym$label ## Not run: writeHeinzNodes(network=chipGraph, file="lymphoma_nodes_001", node.scores=score)
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