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08BarConect.R
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08BarConect.R
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rm(list = ls())
#Did you change it to your base location?
baseDir="~/LeadNPC/"
setwd(baseDir)
source(file = "bin/00base.R")
load("./Data/allTranscriptogramers80")
load("./Data/tfs.RData")
load("./Data/colors.RData")
#load("./Data/colorsSB.RData")
load("./Data/assocNoDup.RData")
conectDir="tmpGraf/"
library(igraph)
library(RedeR)
library(transcriptogramer)
library(ggplot2)
library(purrr)
#intersecção dos clusteres
load(file = "./Data/clusteres.RData")
c1<-clusteres$T1
c2<-clusteres$T2
load(file = "./Data/cl12.RData")
load(file='./Data/clusters12.RData')
#Grapho master ----
gMaster <- graph_from_data_frame(assocNoDup, directed = F)
V(gMaster)$nodeShape <- "CIRCLE"
E(gMaster)$edgeColor<-"#c9c9c9ff"
cltRef<-data.frame(c1=c1,c2=c2)
# Intervalo 2 ----
i=1
netMean<-data.frame(time=numeric(), cl=numeric(), mean=numeric())
for(i in 1:11){
nodesP<-subset(clusters12,Clust2==i,select = c("Protein") )
nodesP$Protein<-as.character(nodesP$Protein)
F0<-induced_subgraph(graph=gMaster, v=V(gMaster)[V(gMaster)$name %in% nodesP$Protein])
degree<-igraph::degree(F0, mode = "all", loops = F)
netMean<-rbind(netMean,c(2,i,mean(degree)))
c0 <- degree_distribution(F0)
cl<-data.frame(degree=seq(0,(length(c0)-1)),
p0=c0)
if(nrow(cl)<100){
step<-1
}else{
step<-round(nrow(cl)/100,0)
}
clu3<-cl[c(1),]
j=1
for(j in seq(2,nrow(cl)-step,step)){
clu3<-rbind(clu3,c(j,sum(cl[j:(j+step),2])))
}
clu3<-rbind(clu3,c(nrow(cl),sum(cl[j:nrow(cl),2])))
clu3<-rbind(clu3,c(nrow(cl)+step,0))
cl<-clu3
cl$p0[cl$p0==0]<- 1e-15
cl2<-data.frame(degree=log10(cl$degree),p0=log10(cl$p0))
cl2$degree[cl2$degree==-Inf]<-0
smoothedLine<-stats::smooth.spline(cl2)
cl2 <- data.frame(degree = smoothedLine$x, p0 = smoothedLine$y)
cl2$p0[cl2$p0 < -15]<- -15
g<- ggplot()+
geom_line(data=cl2,aes(degree,p0))+
geom_hline(yintercept = -15,lty=3, col="red")+
scale_y_continuous(breaks = c(-12.5,-10,-5,0))+
xlab("Degrees of Connectivity (log)")+
ylab("P(k) (log)")+
annotate(geom="text", x=0, y=-15, label="-Inf",
color="red",hjust = 3)+
coord_cartesian(clip = 'off' ) +
theme_bw()
# g
svg(file = paste0(conectDir,"t2c",
i,".svg"),
width = 11,height = 8)
plot(g)
dev.off()
}
# Intervalo 1 ----
i=1
for(i in 1:11){
nodesP<-subset(clusters12,Clust1==i,select = c("Protein") )
nodesP$Protein<-as.character(nodesP$Protein)
F0<-induced_subgraph(graph=gMaster, v=V(gMaster)[V(gMaster)$name %in% nodesP$Protein])
c0 <- degree_distribution(F0)
cl<-data.frame(degree=seq(0,(length(c0)-1)),
p0=c0)
if(nrow(cl)<100){
step<-1
}else{
step<-round(nrow(cl)/100,0)
}
#clu3<-cl[c(1,nrow(cl)),]
clu3<-cl[c(1),]
j=1
for(j in seq(2,nrow(cl)-step,step)){
clu3<-rbind(clu3,c(j,sum(cl[j:(j+step),2])))
}
clu3<-rbind(clu3,c(nrow(cl),sum(cl[j:nrow(cl),2])))
clu3<-rbind(clu3,c(nrow(cl)+step,0))
cl<-clu3
cl1<-clu3
cl$p0[cl$p0==0]<- 1e-15
cl2<-data.frame(degree=log10(cl$degree),p0=log10(cl$p0))
cl3<-data.frame(degree=log10(cl$degree),p0=cl$p0)
cl2$degree[cl2$degree==-Inf]<-0
cl3$degree[cl3$degree==-Inf]<-0
smoothedLine<-stats::smooth.spline(cl1)
cl1 <- data.frame(degree = smoothedLine$x, p0 = smoothedLine$y)
smoothedLine<-stats::smooth.spline(cl2)
cl2 <- data.frame(degree = smoothedLine$x, p0 = smoothedLine$y)
cl2$p0[cl2$p0 < -15]<- -15
smoothedLine<-stats::smooth.spline(cl3)
cl3 <- data.frame(degree = smoothedLine$x, p0 = smoothedLine$y)
g<- ggplot()+
geom_line(data=cl3,aes(degree,p0))+
xlab("Degrees of Connectivity (log)")+
ylab("P(k)")+
theme_bw()
svg(file = paste0(conectDir,"t1c",
i,"logX.svg"),
width = 11,height = 8)
plot(g)
dev.off()
g<- ggplot()+
geom_line(data=cl1,aes(degree,p0))+
xlab("Degrees of Connectivity")+
ylab("P(k)")+
theme_bw()
svg(file = paste0(conectDir,"t1c",
i,".svg"),
width = 11,height = 8)
plot(g)
dev.off()
g<- ggplot()+
geom_line(data=cl2,aes(degree,p0))+
geom_hline(yintercept = -15,lty=3, col="red")+
scale_y_continuous(breaks = c(-12.5,-10,-5,0))+
xlab("Degrees of Connectivity (log)")+
ylab("P(k) (log)")+
annotate(geom="text", x=0, y=-15, label="-Inf",
color="red",hjust = 3)+
coord_cartesian(clip = 'off' ) +
theme_bw()
svg(file = paste0(conectDir,"t1c",
i,"logXY.svg"),
width = 11,height = 8)
plot(g)
dev.off()
}
lightColor = function(color){
if(class(color) != "character"){
cat("Color must be a string.")
}
R<-paste0("0x",substr(color,2,3))
G<-paste0("0x",substr(color,4,5))
B<-paste0("0x",substr(color,6,7))
r<-ifelse(strtoi(R)<=127,strtoi(R)+128,255)
g<-ifelse(strtoi(G)<=127,strtoi(G)+128,255)
b<-ifelse(strtoi(B)<=127,strtoi(B)+128,255)
color2<-paste0("#",
sprintf("%x",r),
sprintf("%x",g),
sprintf("%x",b))
return(color2)
}
# conectiv média ----
#rede pai
cl=7
netMean<-data.frame(time=numeric(), cl=numeric(), mean=numeric())
time=1
for(time in 1:2){
clTmp<-na.exclude(clusters12[,c(1,time+2)])
for(cl in 1:11){
nodesP<-clTmp[clTmp[2]==cl,1]
nodesP<-as.character(nodesP)
# subAssoc<-association7[association7$p1%in%nodesP &
# association7$p2%in%nodesP,]
F0<-induced_subgraph(graph=gMaster, v=V(gMaster)[V(gMaster)$name %in% nodesP])
degree<-igraph::degree(F0, mode = "out", loops = F)
netMean[nrow(netMean)+1,] <- c(time,cl,mean(degree))
}
}
rm(clTmp)
conecDir="./figures/"
ref2=3
# clusters 1 p/ 1----
#somente quem é 1 para 1
for(ref2 in c(2,3,4,5,6,7,9,10,11)){
if(nrow(na.exclude(cltRef[cltRef$c2 == ref2,]))==0){
ref1=0
}else{
ref1<-cltRef$c1[cltRef$c2 == ref2]
ref1<-na.exclude(ref1)
}
grData<-data.frame(cl=numeric(), media=numeric(),cor=character(),
stringsAsFactors = F)
#parametros de cor tempo1
cor<-substr(toupper(color[[1]][ref1]),1,7)
if(ref1 == 0){
grData[nrow(grData)+1,] <- data.frame(1,
0,
"#000000",
stringsAsFactors = F)
}else{
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref1],
cor,
stringsAsFactors = F)
}
#parametros de cor tempo2
cor<-toupper(color[[2]][ref2])
# cor<-lightColor(toupper(color[[2]][ref2]))
grData[nrow(grData)+1,] <- data.frame(2,
netMean$mean[netMean$time==2 &
netMean$cl == ref2],
cor,
stringsAsFactors = F)
theme_new <- theme_set(theme_bw(base_size = 50))
theme_new <- theme_update(axis.title.x = element_text(size =30),
axis.title.y = element_text(size =30),
axis.text.x = element_text(size =50),
axis.text.y = element_text(size =50))
#grData$media2<-numeric(grData$media)
#usar em caso de lightColor()
#cor<-grData$cor
cor<-c(cor,cor)
g <- ggplot(grData, aes(x=as.factor(cl),y=media))+
#scale_x_continuous(limits = c(0.5,2.5))+
scale_y_continuous(limits=c(0,max(netMean$mean)))+
xlab("Interval")+
ylab("<k>")+
geom_bar(aes(fill=cor),stat = "identity", col=1, width = 0.45)+
scale_fill_manual(values=cor, guide=F)
plot(g)
svg(width = 11,height = 8.95,file = paste0(conecDir,"avgConec",ref2,".svg"))
suppressMessages(graphics::plot(g))
dev.off()
}
#clusteres 1 e 8
# cluster 1 ----
ref2<-1
ref11<-1
ref12<-2
ref13<-3
grData<-data.frame(cl=numeric(), media=numeric(),cor=character(),
stringsAsFactors = F)
#parametros de cor tempo1
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref11],
substr(toupper(color[[1]][ref11]),1,7),
stringsAsFactors = F)
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref12],
substr(toupper(color[[1]][ref12]),1,7),
stringsAsFactors = F)
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref13],
substr(toupper(color[[1]][ref13]),1,7),
stringsAsFactors = F)
#parametros de cor tempo2
grData[nrow(grData)+1,] <- data.frame(2,
netMean$mean[netMean$time==2 &
netMean$cl == ref2],
# lightColor(toupper(color[[2]][ref2])),
# stringsAsFactors = F)
toupper(color[[2]][ref2]),
stringsAsFactors = F)
theme_new <- theme_set(theme_bw(base_size = 50))
theme_new <- theme_update(axis.title.x = element_text(size =30),
axis.title.y = element_text(size =30),
axis.text.x = element_text(size =50),
axis.text.y = element_text(size =50))
#grData$media2<-numeric(grData$media)
cor<-grData$cor
g <- ggplot()+
scale_x_discrete(breaks = c(1,2))+
scale_y_continuous(limits=c(0,max(netMean$mean)))+
xlab("Interval")+
ylab("<k>")+
geom_bar(data=grData[1:3,], aes(x=as.factor(cl),y=media),
fill = c(cor[1],cor[2],cor[3]),
stat = "identity", col=1, width = 0.45)+
geom_bar(data=grData[4,], aes(x=as.factor(cl),y=media),
fill = c(cor[4]),
stat = "identity", col=1, width = 0.45)
#geom_bar(aes(fill=cor),stat = "identity", col=1, width = 0.45)+
#scale_fill_manual(values=grData$cor, guide=F)
plot(g)
svg(width = 11,height = 8.95,file = paste0(conecDir,"avgConec1.svg"))
suppressMessages(graphics::plot(g))
dev.off()
# cluster 8 ----
ref2<-8
ref11<-9
ref12<-10
grData<-data.frame(cl=numeric(), media=numeric(),cor=character(),
stringsAsFactors = F)
#parametros de cor tempo1
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref11],
substr(toupper(color[[1]][ref11]),1,7),
stringsAsFactors = F)
grData[nrow(grData)+1,] <- data.frame(1,
netMean$mean[netMean$time==1 &
netMean$cl == ref12],
substr(toupper(color[[1]][ref12]),1,7),
stringsAsFactors = F)
#parametros de cor tempo2
grData[nrow(grData)+1,] <- data.frame(2,
netMean$mean[netMean$time==2 &
netMean$cl == ref2],
# lightColor(toupper(color[[2]][ref2])),
# stringsAsFactors = F)
toupper(color[[2]][ref2]),
stringsAsFactors = F)
theme_new <- theme_set(theme_bw(base_size = 50))
theme_new <- theme_update(axis.title.x = element_text(size =30),
axis.title.y = element_text(size =30),
axis.text.x = element_text(size =50),
axis.text.y = element_text(size =50))
#grData$media2<-numeric(grData$media)
cor<-grData$cor
g <- ggplot()+
scale_x_discrete(breaks = c(1,2))+
scale_y_continuous(limits=c(0,max(netMean$mean)))+
xlab("Interval")+
ylab("<k>")+
geom_bar(data=grData[1:2,], aes(x=as.factor(cl),y=media),
fill = c(cor[1],cor[2]),
stat = "identity", col=1, width = 0.45)+
geom_bar(data=grData[3,], aes(x=as.factor(cl),y=media),
fill = c(cor[3]),
stat = "identity", col=1, width = 0.45)
#geom_bar(aes(fill=cor),stat = "identity", col=1, width = 0.45)+
#scale_fill_manual(values=grData$cor, guide=F)
plot(g)
svg(width = 11,height = 8.95,file = paste0(conecDir,"avgConec8.svg"))
suppressMessages(graphics::plot(g))
dev.off()