###########################################################################
#
#   Supplementary file 1: R codes for identifying differentially correlated edges for MS 
#
############################################################################
#read in the expression data: expMS (frma pre-processed) and the protein-to-protein intersection information downloaded fro the string database: protein.links.v110.txt. 

new.junk1<-read.table("~/Downloads/protein.links.v11.0.txt", header=TRUE)

#try on string data 
g<-as.character(union(unique(new.junk1[,1]), unique(new.junk1[,2])))

PPI<-matrix(0,nrow=length(g),ncol=length(g),dimnames=list(g,g))
for(i in 1:dim(PPI)[1]){
   tmp<-as.character(new.junk1[as.character(new.junk1[,1])==rownames(PPI)[i],2])
   PPI[i,tmp]<-rep(1,length(tmp))
}

#

PPI.try<-matrix(0,nrow=length(g),ncol=length(g),dimnames=list(g,g))

for(i in 1:dim(PPI.try)[1]){
    tmp<-as.character(new.junk1[as.character(new.junk1[,1])==rownames(PPI.try)[i],2])
    PPI.try[i,tmp]<-as.double(new.junk1[new.junk1[,1]==g[i] & new.junk1[,2]%in%tmp, 3])

}


subject<-rep(1:25, each=5)
status<-rep(c(0,1,1,0,1,0,0,0,1, 0,0,0,0,1,0,1,0,0,1,0,0,0,0,1,1), each=5)
status1<-c(0,1,1,0,1,0,0,0,1, 0,0,0,0,1,0,1,0,0,1,0,0,0,0,1,1)

PPI.try.MS<-PPI.try[intersect(rownames(PPI.try), rownames(expMS)), intersect(rownames(PPI.try), rownames(expMS))]


#for time 1 
c=0.6

PPI.new<-apply(PPI.try.MS, 1, function(x){ifelse(x>600, 1, 0)})
rsum<-rowSums(PPI.new)
PPI.new1<-PPI.new[which(rsum>0),which(rsum>0) ]

status1<-status1[-c(1,4, 8, 10, 13, 18, 20)]
time<-rep(1:5, 18)


#time point 1 
expMS.t1<-expMS[,which(time==1)]
expMS.t1<-expMS.t1[,-c(1,4, 8, 10, 13, 18, 20) ]
cor.t1.r<-cor(t(expMS.t1[, which(status1==1)]), method=”spearman”)
cor.t1.nr<-cor(t(expMS.t1[, which(status1==0)]), method=”spearman”)

diff.t1<-apply((cor.t1.r-cor.t1.nr)*PPI.new1, 1,  function(x){ifelse(x>c, 1, ifelse(x<0-c, -1, 0))})

diff.t11<-diff.t1[which(rowSums(diff.t1)!=0), which(rowSums(diff.t1)!=0)] 
junk<-list()
for(i in 1:dim(diff.t11)[1]){
	junk[[i]]<-names(diff.t11[i,])[which(diff.t11[i,]!=0)]
}

names(junk)<-rownames(diff.t11)
junk.length<-sapply(junk, length)
junk1<-junk[which(junk.length!=0)]
junk.length<-junk.length[which(junk.length!=0)]


junk2<-NULL
for (i in 1:length(junk1)){
	junk2<-c(junk2, rep(names(junk1)[i], junk.length[i]))
}
junk3<-unlist(junk1)
pair.t1<-paste(junk2, junk3, sep="_")



#time point 2 
expMS.t2<-expMS[,which(time==2)]
expMS.t2<-expMS.t2[,-c(1,4, 8, 10, 13, 18, 20) ]
cor.t2.r<-cor(t(expMS.t2[, which(status1==1)]), method=”spearman”)
cor.t2.nr<-cor(t(expMS.t2[, which(status1==0)]), method=”spearman”)

diff.t2<-apply((cor.t2.r-cor.t2.nr)*PPI.new1,  1,  function(x){ifelse(x>c, 1, ifelse(x<0-c, -1, 0))})

diff.t11<-diff.t2[which(rowSums(diff.t2)!=0), which(rowSums(diff.t2)!=0)] 
junk<-list()
for(i in 1:dim(diff.t11)[1]){
	junk[[i]]<-names(diff.t11[i,])[which(diff.t11[i,]!=0)]
}

names(junk)<-rownames(diff.t11)
junk.length<-sapply(junk, length)
junk1<-junk[which(junk.length!=0)]
junk.length<-junk.length[which(junk.length!=0)]


junk2<-NULL
for (i in 1:length(junk1)){
	junk2<-c(junk2, rep(names(junk1)[i], junk.length[i]))
}
junk3<-unlist(junk1)

pair.t2<-paste(junk2, junk3, sep="_")



#time 3 
expMS.t3<-expMS[,which(time==3)]
expMS.t3<-expMS.t3[,-c(1,4, 8, 10, 13, 18, 20) ]
cor.t3.r<-cor(t(expMS.t3[, which(status1==1)]), method=”spearman”)
cor.t3.nr<-cor(t(expMS.t3[, which(status1==0)]) , method=”spearman”)
diff.t3<-apply((cor.t3.r-cor.t3.nr)*PPI.new1, 1, function(x){ifelse(x>c, 1, ifelse(x<0-c, -1, 0))})


diff.t11<-diff.t3[which(rowSums(diff.t3)!=0), which(rowSums(diff.t3)!=0)] 
junk<-list()
for(i in 1:dim(diff.t11)[1]){
	junk[[i]]<-names(diff.t11[i,])[which(diff.t11[i,]!=0)]
}

names(junk)<-rownames(diff.t11)
junk.length<-sapply(junk, length)
junk1<-junk[which(junk.length!=0)]
junk.length<-junk.length[which(junk.length!=0)]


junk2<-NULL
for (i in 1:length(junk1)){
	junk2<-c(junk2, rep(names(junk1)[i], junk.length[i]))
}
junk3<-unlist(junk1)

pair.t3<-paste(junk2, junk3, sep="_")


#time 4 
expMS.t4<-expMS[,which(time==4)]
expMS.t4<-expMS.t4[,-c(1,4, 8, 10, 13, 18, 20) ]

cor.t4.r<-cor(t(expMS.t4[, which(status1==1)]), method=”spearman”)
cor.t4.nr<-cor(t(expMS.t4[, which(status1==0)]), method=”spearman”)
diff.t4<-apply((cor.t4.r-cor.t4.nr)*PPI.new1, 1, function(x){ifelse(x>c, 1, ifelse(x<0-c, -1, 0))})

diff.t11<-diff.t4[which(rowSums(diff.t4)!=0), which(rowSums(diff.t4)!=0)] 
junk<-list()
for(i in 1:dim(diff.t11)[1]){
	junk[[i]]<-names(diff.t11[i,])[which(diff.t11[i,]!=0)]
}

names(junk)<-rownames(diff.t11)
junk.length<-sapply(junk, length)
junk1<-junk[which(junk.length!=0)]
junk.length<-junk.length[which(junk.length!=0)]


junk2<-NULL
for (i in 1:length(junk1)){
	junk2<-c(junk2, rep(names(junk1)[i], junk.length[i]))
}

junk3<-unlist(junk1)
pair.t4<-paste(junk2, junk3, sep="_")


#time 5 
expMS.t5<-expMS[,which(time==5)]
expMS.t5<-expMS.t5[,-c(1,4, 8, 10, 13, 18, 20) ]
cor.t5.r<-cor(t(expMS.t5[, which(status1==1)]), method=”spearman”)
cor.t5.nr<-cor(t(expMS.t5[, which(status1==0)]), method=”spearman”)
diff.t5<-apply((cor.t5.r-cor.t5.nr)*PPI.new1, 1, function(x){ifelse(x>c, 1, ifelse(x<0-c, -1, 0))})


diff.t11<-diff.t5[which(rowSums(diff.t5)!=0), which(rowSums(diff.t5)!=0)] 
junk<-list()
for(i in 1:dim(diff.t11)[1]){
	junk[[i]]<-names(diff.t11[i,])[which(diff.t11[i,]!=0)]
}

names(junk)<-rownames(diff.t11)
junk.length<-sapply(junk, length)
junk1<-junk[which(junk.length!=0)]
junk.length<-junk.length[which(junk.length!=0)]


junk2<-NULL
for (i in 1:length(junk1)){
	junk2<-c(junk2, rep(names(junk1)[i], junk.length[i]))
}

junk3<-unlist(junk1)
pair.t5<-paste(junk2, junk3, sep="_")

comm.pair<-(unique(intersect(intersect(intersect(intersect(pair.t1, pair.t2), pair.t3), pair.t4), pair.t5)))

junk1<-unlist(strsplit(comm.pair, "_"))


#get the values for different time points 

junk.list<-NULL 
for (j in 1:(length(junk1)/2-1)){
	junk.list<-rbind(junk.list, c(junk1[j*2+1], junk1[j*2+2], round(cor.t1.r[junk1[j*2+1],junk1[j*2+2] ],3), round(cor.t1.nr[junk1[j*2+1],junk1[j*2+2]],3), round(cor.t2.r[junk1[j*2+1],junk1[j*2+2] ],3), round(cor.t2.nr[junk1[j*2+1],junk1[j*2+2]],3), round(cor.t3.r[junk1[j*2+1],junk1[j*2+2] ],3), round(cor.t3.nr[junk1[j*2+1],junk1[j*2+2]],3), round(cor.t4.r[junk1[j*2+1],junk1[j*2+2] ],3), round(cor.t4.nr[junk1[j*2+1],junk1[j*2+2]],3), round(cor.t5.r[junk1[j*2+1],junk1[j*2+2] ],3), round(cor.t5.nr[junk1[j*2+1],junk1[j*2+2]],3)))
	
}

junk<-data.frame(p11=junk.list[,1], p21=junk.list[,2], stringsAsFactors=FALSE)
junk<-transform(junk, T1=ifelse(p11<=p21, p11, p21))
junk<-transform(junk, T2=ifelse(p11>p21, p11, p21))
junk<-cbind(junk, junk.list[,-c(1:2)])
junk<-junk[,-c(1:2)]
junk_dup<-junk[!duplicated(junk), ]
write.csv(junk_dup, file="junk_dup_600_06_18samples.csv")