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6_heatmap_celltypes.R
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library(gplots)
library(tidyverse)
library(reshape2)
library(ggplot2)
outFolder="6_celltype_cor_heatmap_plot_Roger/"
system(paste0("mkdir -p ", outFolder))
# cell type labels
cell.type.annotation<-read.delim("cell.type.annotation.v2.txt")
clust2Names<-cell.type.annotation$Potential.final #c("Stromal-1","Macrophage-2","Macrophage-1","Endothelial-1","Monocyte","CD4_T-cell","Decidual","CD8_T-cell","LED","Stromal-2","ILC","NK-cell","Smooth muscle cells-1","Stromal Fibroblast","Macrophage-3","Endothelial-2","DC","Smooth muscle cells-2","EVT","Plasmablast","Smooth muscle cells","Macrophage-4","B-cell","Unciliated Epithelial")
clust2Names<-paste0(cell.type.annotation$Cluster,":",clust2Names)
names(clust2Names)<-as.character(cell.type.annotation$Cluster)
#cell.type.annotation$color<-as.character(cluster.Colors[1:33])
#write_tsv(cell.type.annotation,file="cell.type.annotation.v2.tsv")
# union of DE genes across cell types
res_de <-read_tsv("./7_outputs_DESeq_ConditionsByCluster_with_covidcontrol_res1.0_library/SIG.combined.2022-03-29.tsv")
res_de <- res_de %>% separate(cname,c("Location","Cluster","Origin"),sep="_",remove=FALSE)
de_gene<-unique(res_de$kbid)
res_de$Cell_type<-clust2Names[res_de$Cluster]
res_de$cname<-paste0(res_de$Cell_type,"_",res_de$Location,"_",res_de$Origin)
# calculating correlation based on union of DE genes
res <-read_tsv("7_outputs_DESeq_ConditionsByCluster_with_covidcontrol_res1.0_library/ALL.combined.2022-03-29.tsv")
res<-res %>% filter(!is.na(log2FoldChange) & !is.na(padj))
res<-res %>% filter (kbid %in% de_gene)
res <- res %>% separate(cname,c("Location","Cluster","Origin"),sep="_",remove=FALSE)
res$Cell_type<-clust2Names[res$Cluster]
res$cname<-paste0(res$Cell_type,"_",res$Location,"_",res$Origin)
### RPR changed this line. I think this will solve the problem of not getting the same plot.
##clusters<-unique(res_de$cname)
###clusters<-unique(res$cname)
### RPR 2023/02/21 Additionally changed this to remove small clusters.
tt <- table(res_de$cname)
clusters <- names(which(tt>10))
# clusters_location<-sapply(clusters,function(x){
# y<-unlist(strsplit(x,"_"))
# return(y[length(y)])
#
# })
# clusters_location<-clusters_location[order(clusters_location,decreasing = TRUE)]
# clusters<-names(clusters_location)
cor_matrix<-matrix(NA,nrow=length(clusters),ncol=length(clusters))
for (i in 1:length(clusters))
{
for (j in 1: length(clusters))
{
resi<-res %>% dplyr::filter(cname == clusters[i]) %>% dplyr::select(kbid,log2FoldChange,lfcSE)
resj<-res %>% dplyr::filter(cname == clusters[j])%>% dplyr::select(kbid,log2FoldChange,lfcSE)
colnames(resj)<-c("kbid","log2FoldChange2","lfcSE2")
res_intersect<-resi%>% inner_join(resj)
res_intersect<-res_intersect%>% dplyr::select(log2FoldChange,log2FoldChange2)
if(nrow(res_intersect)>5)
{
cr<-cor(res_intersect)[1,2]
cor_matrix[i,j]<-cr
cor_matrix[j,i]<-cr
}
}
}
rownames(cor_matrix)<-clusters
colnames(cor_matrix)<-clusters
write_rds(cor_matrix,file=paste0(outFolder,"cor_matrix.rds"))
write_rds(cor_matrix,file=paste0(outFolder,"cor_matrix_all.rds"))
# heatmap plot
library(pheatmap)
fname=paste0(outFolder,"heatmap_celltype_cor.pdf");
pdf(fname,width=8,height=8)
paletteLength<-50
my_palette <- colorRampPalette(colors = c("#E8F4F8","white", "#A50021"))(n = paletteLength)
myBreaks <- c(seq(min(cor_matrix), 0, length.out=ceiling(paletteLength/2) ),
seq(max(cor_matrix)/paletteLength, max(cor_matrix), length.out=floor(paletteLength/2)))
#myBreaks <- c(seq( min(cor_matrix),0,length.out=20), seq(0,max(cor_matrix), length.out=30) )
pheatmap(cor_matrix,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize=12)
dev.off()
fname=paste0(outFolder,"heatmap_celltype_cor_all.pdf");
pdf(fname,width=15,height=15)
paletteLength<-50
my_palette <- colorRampPalette(colors = c("#E8F4F8","white", "#A50021"))(n = paletteLength)
myBreaks <- c(seq(min(cor_matrix), 0, length.out=ceiling(paletteLength/2) ),
seq(max(cor_matrix)/paletteLength, max(cor_matrix), length.out=floor(paletteLength/2)))
#myBreaks <- c(seq( min(cor_matrix),0,length.out=20), seq(0,max(cor_matrix), length.out=30) )
pheatmap(cor_matrix,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize=10)
dev.off()
# fname=paste0(outFolder,"heatmap_celltype_cor2.pdf");
# pdf(fname,width=30,height=30)
#
# pheatmap(cor_matrix,cluster_rows=TRUE,fontsize=20)
# dev.off()
### new plot ####
# library(pheatmap)
#
# fname=paste0(outFolder,"heatmap_celltype_cor3.pdf");
# pdf(fname,width=38,height=28)
# #pheatmap(cor_matrix,cluster_rows=TRUE,cluster_cols=TRUE,scale="none")
# #my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 201)
# paletteLength<-30
# # my_palette <- colorRampPalette(colors = c("#333399", "white", "#A50021"))(n = paletteLength+1)
# # myBreaks <- c(seq(min(cor_matrix),0, length.out=ceiling(paletteLength/2) + 1),
# # seq(max(cor_matrix)/paletteLength, max(cor_matrix), length.out=floor(paletteLength/2)))
#
# my_palette <- colorRampPalette(colors = c("#D8EAF0","white", "#A50021"))(n = paletteLength+1)
# myBreaks <- c(seq(min(cor_matrix),0, length.out=ceiling(paletteLength/2) + 1),
# seq(max(cor_matrix)/paletteLength, max(cor_matrix), length.out=floor(paletteLength/2)))
#
# pheatmap(cor_matrix,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize =10)
# dev.off()
############
clusters_location<-sapply(clusters,function(x){
y<-unlist(strsplit(x,"_"))
return(y[2])
})
clusters_number<-sapply(clusters,function(x){
y<-unlist(strsplit(x,"_"))
y<-unlist(strsplit(y,":"))
return(as.numeric(y[1]))
})
# clusters_number<-clusters_number[order(clusters_number,decreasing = FALSE)]
#
# cor_matrix<-cor_matrix[names(clusters_number),]
# cor_matrix_cervix<-cor_matrix[,clusters_location[colnames(cor_matrix)]=="Cervix"]
########################################################
# Same cell type across locations
# Decidua-Cervix
# Decidua-Myometrium
# Myometrium-Cervix
########################################################
CAM<-names(clusters_location)[which(clusters_location =="CAM")]
PVBP<-names(clusters_location)[which(clusters_location =="PVBP")]
#D_C<-names(clusters_location)[which(clusters_location !="Myometrium")]
cor_matrix_CAM_PVBP<-cor_matrix[CAM,PVBP]
library(pheatmap)
fname=paste0(outFolder,"heatmap_celltype_cor_CAM_PVBP.pdf");
pdf(fname,width=5,height=6)
paletteLength<-50
my_palette <- colorRampPalette(colors = c("#E8F4F8","white", "#A50021"))(n = paletteLength)
myBreaks <- c(seq(min(cor_matrix_CAM_PVBP), 0, length.out=ceiling(paletteLength/2) ),
seq(max(cor_matrix_CAM_PVBP)/paletteLength, max(cor_matrix_CAM_PVBP), length.out=floor(paletteLength/2)))
#myBreaks <- c(seq( min(cor_matrix),0,length.out=20), seq(0,max(cor_matrix), length.out=30) )
pheatmap(cor_matrix_CAM_PVBP,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize=10)
dev.off()
# pdf(paste0(outFolder,"boxplot_celltype_locations.pdf"),width=3,height = 3)
# ggplot(data_locations,aes(x=Location, y=Correlation,fill=Location)) +
# geom_boxplot()+
# xlab("")+
# scale_fill_manual(values=c("Decidua-Cervix"="#74AF81","Decidua-Myometrium"="#B46FB5","Myometrium-Cervix"="#99BE7F") )+
# theme_bw()+
# theme(legend.position="none",axis.text.x = element_text(angle = 90, hjust=1,vjust = 0.2))
# #theme(axis.text=element_text(size=30))
# #scale_color_manual(values=c("red", "green", "blue"))
# #facet_wrap(~Location, scale="free")
# dev.off()
########################################################
# within location across cell types
cor_matrix_CAM<-cor_matrix[CAM,CAM]
cor_matrix_PVBP<-cor_matrix[PVBP,PVBP]
library(pheatmap)
fname=paste0(outFolder,"heatmap_celltype_cor_CAM.pdf");
pdf(fname,width=12,height=13)
paletteLength<-50
my_palette <- colorRampPalette(colors = c("#E8F4F8", "white", "#A50021"))(n = paletteLength)
myBreaks <- c(seq(min(cor_matrix_CAM), 0, length.out=ceiling(paletteLength/2) ),
seq(max(cor_matrix_CAM)/paletteLength, max(cor_matrix_CAM), length.out=floor(paletteLength/2)))
pheatmap(cor_matrix_CAM,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize=10)
dev.off()
# fname=paste0(outFolder,"heatmap_celltype_cor_PVBP.pdf");
# pdf(fname,width=5,height=5)
# paletteLength<-10
# my_palette <- colorRampPalette(colors = c("#E8F4F8", "white", "#A50021"))(n = paletteLength)
# myBreaks <- c(seq(min(cor_matrix_PVBP), 0, length.out=ceiling(paletteLength/2) ),
# seq(max(cor_matrix_PVBP)/paletteLength, max(cor_matrix_PVBP), length.out=floor(paletteLength/2)))
# pheatmap(cor_matrix_PVBP,cluster_rows=TRUE,color=my_palette,scale="none",breaks=myBreaks,fontsize=10)
# dev.off()