R/writeNetwork.R

In CellNOptR: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

#
#  This file is part of the CNO software
#
#  Copyright (c) 2011-2012 - EMBL - European Bioinformatics Institute
#
#  File author(s): CNO developers (cno-dev@ebi.ac.uk)
#
#  Distributed under the GPLv3 License.
#  See accompanying file LICENSE.txt or copy at
#      http://www.gnu.org/licenses/gpl-3.0.html
#
#  CNO website: http://www.cellnopt.org
#
##############################################################################
# $Id: writeNetwork.R 3155 2013-01-09 15:24:58Z cokelaer $
##the global function is still called writeNetwork and still needs the same arguments
#(modelComprExpanded, optimResT1, optimResT2, modelOriginal, CNOlist), but it is divided into:
#    -a function writeSNetworkW that does the actual writing to files,
#    -a function that gets the info for the sif and dot files
writeNetwork<-function(modelOriginal, modelComprExpanded, optimResT1,
    optimResT2=NA, CNOlist, tag=NULL, verbose=FALSE)
{

    nwInfo<-getNetworkInfo(
        modelOriginal=modelOriginal,
        modelComprExpanded=modelComprExpanded,
        optimResT1=optimResT1,
        optimResT2=optimResT2,
        CNOlist=CNOlist,verbose=verbose)

    writeNetworkW(
        dN=nwInfo$dN,
        dM=nwInfo$dM,
        modelOriginal=modelOriginal,
        sifFile=nwInfo$sifFile,
        EAweights=nwInfo$EAweights,
        nodesAttr=nwInfo$nodesAttr,
        tag=tag)

    }


#########################################################################
##############these are the functions used above
#########################################################################
#this is the bit that writes
writeNetworkW<-function(dN,dM,modelOriginal,sifFile,EAweights,nodesAttr, tag=NULL){

 create_filename<-function(x, tag=NULL){
        if (is.null(tag)){
            return(x)
        }
        else{
            return(paste(c(tag, "_", x), collapse=""))
        }
    }


    writeDot(
        dotNodes=dN,
        dotMatrix=dM,
        model=modelOriginal,
        filename=create_filename("PKN.dot", tag=tag))

    write.table(
        sifFile[,1:3],
        file=create_filename("PKN.sif", tag=tag),
        row.names=FALSE,col.names=FALSE,quote=FALSE,sep="\t")

    write.table(
        EAweights,
        file=create_filename("TimesPKN.EA", tag=tag),
        row.names=FALSE,col.names="Times",quote=FALSE,sep="\t")

    write.table(
        nodesAttr,
        file=create_filename("nodesPKN.NA", tag=tag),
        row.names=FALSE,col.names="NodesType",quote=FALSE,sep="\t")

    }
############
#this is the bit that produces the info that is needed above
getNetworkInfo<-function(
    modelOriginal,
    modelComprExpanded,
    optimResT1,
    optimResT2,
    CNOlist,
    verbose){

    #These are used to create the string that holds the information about whether an edge is present
#or not (BStimes)
    bString1<-optimResT1$bString

    if(is.na(optimResT2[1])){
        bString2<-optimResT1$bString[which(optimResT1$bString == 0)]
        }else{
            bString2<-optimResT2$bString
            }

#BStimes is a string containing 0,1 and 2 depending on whether the interaction is
#absent, present at t1 or present at t2
    BStimes<-bString1
    BStimes[which(BStimes == 0)]<-bString2*2
#!!! BStimes relates to strings in the compressed and expanded model
    reacs<-modelComprExpanded$reacID
    reacsOriginal<-modelOriginal$reacID

#check if there are ANDs that were split, and if yes, set the score of the original AND
#to the max score of its resulting branches (i.e.the max of the branches, if one branch was present
#at t1 the AND gets 1, same if one was present at t2, if one of the branches was present at T1
#and another one at t2, then the AND gets a score of 3)

    if(names(modelComprExpanded$SplitANDs) != "initialReac"){

        for(i in 1:length(modelComprExpanded$SplitANDs)){

            map<-match(modelComprExpanded$SplitANDs[[i]],reacs)
            mapScore<-BStimes[map]
        #this forces the score to be 3 if a branch was present at t1 and another at t2
            if(any(mapScore == 1) && any(mapScore == 3)) mapScore[1]<-3
            mapScore<-max(mapScore)
            splitAnd<-names(modelComprExpanded$SplitANDs)[i]
            splitAnd<-which(reacs == splitAnd)
            BStimes[splitAnd]<-mapScore

            }

        }

#check if there were ands that were created, and if yes, assign to each branch of the original OR
#the max of the score of the and or of that particular branch

    if(length(modelComprExpanded$newANDs) != 0){

        for(i in 1:length(modelComprExpanded$newANDs)){
            branches<-modelComprExpanded$newANDs[i]
            branchesPos<-match(unlist(branches),reacs)
            BStimes[unlist(branches)]<-pmax(
                BStimes[match(unlist(branches),reacs)],
                BStimes[match(names(modelComprExpanded$newANDs)[i],reacs)])
            }

        }

#The new BStimes vector now contain weights that have been adapted to propagate weights coming
#from new ANDs or split ANDs
#Now create an adjacency list for the compressed/expanded model: col1=in node, col2=out node, col3=weight

findOutput<-function(x){
        sp<-which(x == 1)
        sp<-modelComprExpanded$namesSpecies[sp]
        }

findInput<-function(x){
        sp<-which(x == -1)
        sp<-modelComprExpanded$namesSpecies[sp]
        }

n<-1
adj<-matrix(NA,nrow=(length(reacs)*3),ncol=3)

for(i in 1:length(reacs)){

    input<-findInput(modelComprExpanded$interMat[,i])
    output<-findOutput(modelComprExpanded$interMat[,i])
    weight<-BStimes[i]

    for(j in 1:length(input)){
        adj[n,1]<-input[j]
        adj[n,2]<-output
        adj[n,3]<-weight
        n<-n+1
        }

    }

adj<-adj[-which(is.na(adj[,1])),]

#remove duplicates that arise from new ANDs and split ANDs
adj<-cbind(
    adj[order(adj[,3],decreasing=TRUE),1],
    adj[order(adj[,3],decreasing=TRUE),2],
    adj[order(adj[,3],decreasing=TRUE),3])
adj<-unique(adj)

for(i in 1:dim(unique(adj[,1:2]))[1]){

    findMatch<-apply(adj,1,function(x) all(x[1:2] == adj[i,1:2]))

    if(sum(findMatch) > 1){
        findMatch[which(findMatch == TRUE)[1]]<-FALSE
        adj<-adj[-which(findMatch==TRUE),]
        }

    }

#Now do the same for the original model: col1=in node, col2=out node, col3=reaction #

findOutput<-function(x){
        sp<-which(x == 1)
        sp<-modelOriginal$namesSpecies[sp]
        }

findInput<-function(x){
        sp<-which(x == -1)
        sp<-modelOriginal$namesSpecies[sp]
        }

n<-1
adjOrig<-matrix(NA,nrow=(length(reacsOriginal)*3),ncol=3)

for(i in 1:length(reacsOriginal)){

    input<-findInput(modelOriginal$interMat[,i])
    output<-findOutput(modelOriginal$interMat[,i])

    for(j in 1:length(input)){
        adjOrig[n,1]<-input[j]
        adjOrig[n,2]<-output
        adjOrig[n,3]<-i
        n<-n+1
        }

    }

adjOrig<-adjOrig[-which(is.na(adjOrig[,1])),]

#Go through the adjacency list of the compressed model and find which path is the shortest
#between those species
#this will hold the max weight of anything that has been mapped to this row of adjOrig so far
OrigMap<-rep(0,dim(adjOrig)[1])

for(i in 1:dim(adj)[1]){
#If the row of the compressed adjacency list matches a row of the original adjacency list,
#we just copy the weights
    rowAdj<-adj[i,1:2]
    matchR<-apply(adjOrig[,1:2],1,function(x) all(x == rowAdj))

    if(sum(matchR) > 0){

        OrigMap[which(matchR)]<-max(OrigMap[which(matchR)],adj[i,3])

        }else{

#Otherwise we need to find the shortest path between the nodes in that row of adj, within the rows
#of adjOrig, and map the weights of the row of adj to each of the row of adjOrig that are involved
#in that path
#This only works for paths of length 2 at most: improve this!!!!!
            ins<-which(adjOrig[,1] == adj[i,1])
            outN<-adjOrig[ins,2]
            target<-FALSE
            n<-1

            while(n <= length(outN) && !target){
                outs<-which(adjOrig[,1] == outN[n])
                outN2<-adjOrig[outs,2]

                if(any(outN2 == adj[i,2])){

                    rOut<-which(outN2 == adj[i,2])
                    rOut<-outs[rOut]
                    rIn<-ins[n]
                    n<-n+1
                    target<-TRUE

                    }else{

                        n<-n+1
                        #this sets those variables to NA if the path couldn't be mapped
                        rIn<-NA
                        rOut<-NA

                        }

                }
            #if the path could be mapped, we record the mapping
            if(!is.na(rIn) && !is.na(rOut)){

                OrigMap[rIn]<-max(OrigMap[rIn],adj[i,3])
                OrigMap[rOut]<-max(OrigMap[rOut],adj[i,3])
            #if the path couldn't be mapped (path too long), we print a warning, nad OrigMap
            #stays 0
                }else{

                    if(verbose == TRUE){
                        print("Please be aware that when mapping the scaffold network back to the PKN, compressed paths of length > 2 are ignored.")
                        }

                    }

            }
    }
    BStimesOrig<-cbind(adjOrig[,3],OrigMap)

    for(i in 1:dim(BStimesOrig)[1]){
        BStimesOrig[i,2]<-max(BStimesOrig[i,2],BStimesOrig[which(BStimesOrig[,2] == BStimesOrig[i,1]),2])
        }

    BStimesOrig<-unique(BStimesOrig)
    BStimesOrig<-BStimesOrig[,2]

#These mini functions are used to find the outputs and inputs of a reaction

    findOutput<-function(x){
        sp<-which(x == 1)
        sp<-modelOriginal$namesSpecies[sp]
        }

    reacOutput<-apply(modelOriginal$interMat,2,findOutput)

    findInput<-function(x){
        sp<-which(x == -1)
        sp<-modelOriginal$namesSpecies[sp]
        }

    reacInput<-apply(modelOriginal$interMat,2,findInput)

#This mini function is used to create a reaction label as used in a cystoscape edge attribute file

    createReac<-function(x){
        r<-paste(x[1]," (",x[2],") ",x[3],sep="")
        return(r)
        }

#if the class of reacInput is not a list, then there are no AND gates

    if(class(reacInput) != "list"){

        isNeg<-function(x){
            isNegI<-any(x == 1)
            return(isNegI)
            }

        inpSign<-apply(modelOriginal$notMat,2,isNeg)
        inpSign<-!inpSign
        inpSign[inpSign]<-1
        inpSign[!inpSign]<--1
        sifFile<-cbind(reacInput,inpSign,reacOutput)
        EApresent<-apply(sifFile,1,createReac)
        EAweights<-cbind(EApresent, BStimesOrig)

        }else{

#in this case there are AND gates and so we need to create dummy "and#" nodes
            sifFile<-matrix(0,nrow=200,ncol=4)
            nR<-1
            nANDs<-1

            for(i in 1:length(reacOutput)){

                if(length(reacInput[[i]]) == 1){

                    sifFile[nR,1]<-reacInput[[i]]
                    sifFile[nR,3]<-reacOutput[i]
                    sifFile[nR,2]<-ifelse(any(modelOriginal$notMat[,i] == 1),-1,1)
                    sifFile[nR,4]<-BStimesOrig[i]
                    nR<-nR+1

                    }else{

                        for(inp in 1:length(reacInput[[i]])){

                            sifFile[nR,1]<-reacInput[[i]][inp]
                            sifFile[nR,3]<-paste("and",nANDs,sep="")
                            sifFile[nR,2]<-ifelse(modelOriginal$notMat[inp,i] == 1,-1,1)
                            sifFile[nR,4]<-BStimesOrig[i]
                            nR<-nR+1

                            }

                        sifFile[nR,1]<-paste("and",nANDs,sep="")
                        sifFile[nR,3]<-reacOutput[i]
                        sifFile[nR,2]<-1
                        sifFile[nR,4]<-BStimesOrig[i]
                        nANDs<-nANDs+1
                        nR<-nR+1

                        }
                }

            sifFile<-sifFile[1:(nR-1),]
            EApresent<-apply(sifFile[,1:3],1,createReac)
            EAweights<-cbind(EApresent,sifFile[,4])

            }
    #this bit creates a matrix of reaction that will be used for the dot file
    dM<-cbind(sifFile,BStimesOrig)

    #this mini function makes edge attributes in the format e1 (sign) e2 = attr

    makeEA<-function(x){
        ea<-paste(x[1],"=",x[2])
        return(ea)
        }

    EAweights<-apply(EAweights,1,makeEA)

#write the nodes attributes
    nodesCompr<-modelComprExpanded$speciesCompressed
    indexes<-indexFinder(CNOlist,modelOriginal)
    nodesSig<-modelOriginal$namesSpecies[indexes$signals]
    nodesInh<-modelOriginal$namesSpecies[indexes$inhibited]
    nodesStim<-modelOriginal$namesSpecies[indexes$stimulated]
    nodesNCNO<-findNONC(modelOriginal,indexes)
    nodesAttrNames<-nodesSig
    nodesAttr<-rep("signal",length(nodesSig))

    if(length(nodesInh) != 0){
        nodesAttrNames<-c(nodesAttrNames,nodesInh)
        nodesAttr<-c(nodesAttr,rep("inhibited",length(nodesInh)))
        }

    if(length(nodesStim) != 0){
        nodesAttrNames<-c(nodesAttrNames,nodesStim)
        nodesAttr<-c(nodesAttr,rep("stimulated",length(nodesStim)))
        }

    if(length(nodesNCNO) != 0){
        nodesAttrNames<-c(nodesAttrNames,nodesNCNO)
        nodesAttr<-c(nodesAttr,rep("ncno",length(nodesNCNO)))
        }

    if(length(nodesCompr) != 0){
        nodesAttrNames<-c(nodesAttrNames,nodesCompr)
        nodesAttr<-c(nodesAttr,rep("compressed",length(nodesCompr)))
        }

    nodesAttr<-cbind(nodesAttrNames,nodesAttr)

#this bit creates a matrix of nodes attributes that will be used for the dot file
    dN<-nodesAttr

#this is the node attributes in the format as will be used by cytoscape
    nodesAttr<-apply(nodesAttr,1,makeEA)

#nodes that are neither inh/stim/sig nor NONC will not be in thi snode attribute so I'll add them
    other<-setdiff(modelOriginal$namesSpecies,dN[,1])
    other<-paste(other," = NA",sep="")
    nodesAttr<-c(nodesAttr, other)

#this is the edge attribute matrix that contains, for each edge, whether it is
#absent from the model (0), present at t1(1) or present at t2(2)
    return(list(
        dN=dN,
        dM=dM,
        sifFile=sifFile,
        nodesAttr=nodesAttr,
        EAweights=EAweights))
    }