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GetMatrixOfCausalRelationships <- function(hypothesis, network, idsOfConnectedNodesFromSubgraph){
# Get matrix of Causal Relationships from the network and the IDs of connected nodes
# *** SVN version information ***
# $Date: 2013-01-03 18:03:15 +0000 (Thu, 03 Jan 2013) $
# $Revision: 366 $
# $Author: rild $
# $HeadURL: file:///L:/7000-7499/7412/SVNrepository/trunk/NetworkPredictions/GetMatrixOfCausalRelationships.r $
# Copyright 2012 GSK. All rights reserved
nNodes <- length(idsOfConnectedNodesFromSubgraph)
causalRelationships <- array(0, nNodes)
for (iNode in 1:nNodes){
if (hypothesis == idsOfConnectedNodesFromSubgraph[iNode]){
# Hypothesis node's interaction with itself has to be 1.
causalRelationships[iNode] <- 1
}
else{
shortestPaths <- get.all.shortest.paths(network, hypothesis, idsOfConnectedNodesFromSubgraph[iNode], "out")
numberOfShortestPaths <- length(shortestPaths[[1]])
# Determine interaction type for first path
interactionValue <- DetermineInteractionTypeOfPath(network, shortestPaths[[1]][1])
if (numberOfShortestPaths > 1){
# if there is more than one shortest path, two things can happen:
# 1. they could all agree, in which case we can take any of the values in the vector to populate the data frame
# 2. they could disagree, in this case the interaction given the value 0 (as opposed to 1/-1 for activation/inhibition.
for (counter in 2:numberOfShortestPaths){
interactionValueForAlternativePath <- DetermineInteractionTypeOfPath(network, shortestPaths[[1]][counter])
if (interactionValueForAlternativePath != interactionValue){
interactionValue <- 0
break()
}
}
}
causalRelationships[iNode] <- interactionValue
}
}
return(causalRelationships)
}
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