gc()
library(methods)
library(optparse)
library(Seurat)
library(readr)
library(readxl)
library(fBasics)
library(pastecs)
library(qusage)
library(RColorBrewer)
library(dplyr)
library(viridis)
library(gridExtra)
library(SingleR)
library(sctransform)
library(autothresholdr)
library(ggplot2)

options(bitmapType="cairo")

option_list=list(
  make_option("--p",action="store",default="Biopsy",type='character',help="Project Name"),
  make_option("--s",action="store",default="hu",type='character',help="Species"),
  make_option("--o",action="store",default="pr",type='character',help="Organ")
)
opt=parse_args(OptionParser(option_list=option_list))
rm(option_list)


setwd("../")

source("./r.scripts/sc-TissueMapper_functions.R")
source("./r.scripts/sc-TissueMapper_process.R")

if (opt$s == "hu"){
  hpca.se <- HumanPrimaryCellAtlasData()
  lin.se <- hpca.se
  leu.se <- hpca.se
} else if (opt$s == "mu"){
  igd.se <- ImmGenData()
  #lin.se <- igd.se
  #leu.se <- igd.se
  lin.se <- subset(igd.se,select=(as.numeric(gsub("_","",substr(colnames(igd.se),4,10))) >= 920648 & as.numeric(gsub("_","",substr(colnames(igd.se),4,10))) <= 2112477))
  lin.se <- subset(lin.se,select=!(as.numeric(gsub("_","",substr(colnames(lin.se),4,10))) %in% 1398469:1398471))
  leu.se <- lin.se
}

if (opt$o == "pr" && opt$s == "hu"){
  load("./genesets/Pd.shallow.Rda")
  
  try(
    if (as.numeric(substring(sc10x@version,1,1))<3){
      sc10x <- UpdateSeuratObject(sc10x)
    }
  )
  scDWSpr.se <- as.SingleCellExperiment(sc10x,assay="RNA")
  scDWSpr.se$Lin[scDWSpr.se$Lin == "Unknown"] <- "Leu"
  levels(scDWSpr.se$ident)[levels(scDWSpr.se$ident)=="OE2"] <- "Hillock"
  levels(scDWSpr.se$ident)[levels(scDWSpr.se$ident)=="OE1"] <- "Club"
  rm(sc10x)
}

load("./analysis/sc10x.raw.rda")

sc10x.se <- as.SingleCellExperiment(sc10x)
common <- intersect(rownames(sc10x.se),rownames(lin.se))
lin.se <- lin.se[common,]
sc10x.se <- sc10x.se[common,]
rm(common)

singler.lin <- SingleR(sc10x.se,ref=lin.se,method="cluster",clusters=sc10x.se$integrated_snn_res.5,labels=lin.se$label.fine,BPPARAM=MulticoreParam(workers=10))
sc10x$lin <- singler.lin$labels[match(sc10x.se$integrated_snn_res.5,singler.lin@rownames)]
#singler.lin <- SingleR(sc10x.se,ref=lin.se,method="single",labels=lin.se$label.main,BPPARAM=MulticoreParam(workers=10))
#sc10x$lin <- singler.lin$labels
sc10x$lin[sc10x$lin %in% unique(lin.se@colData[lin.se@colData[,"label.main"] %in% c(
  c("DC","B_cell","Neutrophil","T_cells","Monocyte","Macrophage","NK_cell","Neutrophils","CMP","GMP","MEP","Myelocyte","Pre-B_cell_CD34-","Pro-B_cell_CD34+","Pro-Myelocyte","HSC_-G-CSF","HSC_CD34+"),
  c("Macrophages","Monocytes","B cells","DC","Eosinophils","Neutrophils","T cells","ILC","NK cells","Basophils","Mast cells","Tgd","NKT","B cells, pro","Microglia")
  ),c("label.main","label.fine")])$label.fine] <- "Leu"
sc10x$lin[sc10x$lin %in% unique(lin.se@colData[lin.se@colData[,"label.main"] %in% c(
  c("Endothelial_cells","Erythroblast","Platelets"),
  c("Endothelial cells")
  ),c("label.main","label.fine")])$label.fine] <- "Endo"
sc10x$lin[sc10x$lin %in% unique(lin.se@colData[lin.se@colData[,"label.main"] %in% c(
  c("Smooth_muscle_cells","Fibroblasts","Chondrocytes","Osteoblasts","MSC","Tissue_stem_cells"),
  c("Stromal cells","Fibroblasts")
  ),c("label.main","label.fine")])$label.fine] <- "FMSt"
sc10x$lin[sc10x$lin %in% unique(lin.se@colData[lin.se@colData[,"label.main"] %in% c(
  c("Epithelial_cells","Keratinocytes","Neuroepithelial_cell"),
  c("Epithelial cells")
  ),c("label.main","label.fine")])$label.fine] <- "Epi"
#DimPlot(sc10x,group.by="lin",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")

Idents(sc10x) <- "lin"
sc10x.epi <- subset(sc10x,idents="Epi")
sc10x.fmst <- subset(sc10x,idents="FMSt")
sc10x.st <- subset(sc10x,idents=setdiff(levels(sc10x),"Epi"))
sc10x.leu <- subset(sc10x,idents="Leu")

if (opt$o == "pr" && opt$s == "hu"){
  sc10x.se.epi <- as.SingleCellExperiment(sc10x.epi,assay="RNA")
  scDWSpr.se.epi <- scDWSpr.se[,scDWSpr.se$Lin=="Epi",]
  common <- intersect(rownames(sc10x.se.epi),rownames(scDWSpr.se.epi))
  scDWSpr.se.epi <- scDWSpr.se.epi[common,]
  sc10x.se.epi <- sc10x.se.epi[common,]
  rm(common)
  
  sc10x.se.fmst <- as.SingleCellExperiment(sc10x.fmst,assay="RNA")
  scDWSpr.se.fmst <- scDWSpr.se[,scDWSpr.se$Merge_Epi.dws_St.go %in% c("Fib","SM"),]
  common <- intersect(rownames(sc10x.se.fmst),rownames(scDWSpr.se.fmst))
  scDWSpr.se.fmst <- scDWSpr.se.fmst[common,]
  sc10x.se.fmst <- sc10x.se.fmst[common,]
  rm(common)
  
  singler.epi <- SingleR(sc10x.se.epi,ref=scDWSpr.se.epi,labels=scDWSpr.se.epi$ident,BPPARAM=MulticoreParam(workers=10))
  sc10x.epi$scDWSpr <- singler.epi$labels
  Idents(sc10x.epi) <- "scDWSpr"
  
  singler.fmst <- SingleR(sc10x.se.fmst,ref=scDWSpr.se.fmst,labels=scDWSpr.se.fmst$ident,BPPARAM=MulticoreParam(workers=10))
  sc10x.fmst$scDWSpr <- singler.fmst$labels
  Idents(sc10x.fmst) <- "scDWSpr"
}

sc10x.se.leu <- as.SingleCellExperiment(sc10x.leu,assay="RNA")
leu.se <- leu.se[,leu.se$label.main %in% c("DC","B_cell","Neutrophil","T_cells","Monocyte","Macrophage","NK_cell","Neutrophils","CMP","GMP","MEP","Myelocyte","Pre-B_cell_CD34-","Pro-B_cell_CD34+","Pro-Myelocyte","Macrophages","Monocytes","B cells","Eosinophils","T cells","ILC","NK cells","Basophils","Mast cells","Tgd","NKT","B cells, pro","Microglia")]
common <- intersect(rownames(sc10x.se.leu),rownames(leu.se))
leu.se <- leu.se[common,]
sc10x.se.leu <- sc10x.se.leu[common,]
rm(common)

singler.leu <- SingleR(sc10x.se.leu,ref=leu.se,labels=leu.se$label.main,BPPARAM=MulticoreParam(workers=10))
sc10x.leu$leu <- singler.leu$labels
Idents(sc10x.leu) <- "leu"
#DimPlot(sc10x.leu,group.by="leu",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")

sc10x$pops <- sc10x$lin
sc10x$pops[names(sc10x.leu$leu)] <- sc10x.leu$leu
sc10x.epi$pops <- sc10x.epi$lin
sc10x.fmst$pops <- sc10x.fmst$lin
sc10x.st$pops <- sc10x.st$lin
sc10x.leu$pops <- sc10x.leu$leu
if (opt$o == "pr" && opt$s == "hu"){
  sc10x$pops[names(sc10x.epi$scDWSpr)] <- sc10x.epi$scDWSpr
  sc10x.epi$pops <- sc10x.epi$scDWSpr
  sc10x$pops[names(sc10x.fmst$scDWSpr)] <- sc10x.fmst$scDWSpr
  sc10x.fmst$pops <- sc10x.fmst$scDWSpr
  sc10x.st$pops[names(sc10x.fmst$scDWSpr)] <- sc10x.fmst$scDWSpr
  sc10x$pops[names(sc10x.leu$leu)] <- sc10x.leu$leu
  sc10x.st$pops[names(sc10x.fmst$scDWSpr)] <- sc10x.fmst$scDWSpr
}
#DimPlot(sc10x,group.by="pops",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")

sc10x$leu <- "non-Leu"
sc10x$leu[names(sc10x.leu$leu)] <- sc10x.leu$leu
#DimPlot(sc10x,group.by="leu",reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")

res <- c(seq(0.1,0.5,0.1),0.75,seq(1,5,1))

try({
  results <- scPC(sc10x.epi,pc=100,hpc=0.9,file="epi",print="2")
  sc10x.epi <- results[[1]]
  pc.use.epi <- results[[2]]
  rm(results)
  sc10x.epi <- scCluster(sc10x.epi,res=res,red="pca",dim=pc.use.epi,print="2",folder="epi")
})

try({
  results <- scPC(sc10x.fmst,pc=100,hpc=0.9,file="fmst",print="2")
  sc10x.fmst <- results[[1]]
  pc.use.fmst <- results[[2]]
  rm(results)
  sc10x.fmst <- scCluster(sc10x.fmst,res=res,red="pca",dim=pc.use.fmst,print="2",folder="fmst")
})

try({
  results <- scPC(sc10x.st,pc=100,hpc=0.9,file="st",print="2")
  sc10x.st <- results[[1]]
  pc.use.st <- results[[2]]
  rm(results)
  sc10x.st <- scCluster(sc10x.st,res=res,red="pca",dim=pc.use.st,print="2",folder="st")
})

try({
  results <- scPC(sc10x.leu,pc=100,hpc=0.9,file="leu",print="2")
  sc10x.leu <- results[[1]]
  pc.use.leu <- results[[2]]
  rm(results)
  sc10x.leu <- scCluster(sc10x.leu,res=res,red="pca",dim=pc.use.leu,print="2",folder="leu")
})

if (!dir.exists(paste0("./analysis/vis/singler"))){
  dir.create(paste0("./analysis/vis/singler"))
}

plot <- DimPlot(sc10x,reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")
postscript(paste0("./analysis/vis/singler/UMAP_all.lin.eps"))
print(plot)
dev.off()

Idents(sc10x) <- "pops"
Idents(sc10x.epi) <- "pops"
Idents(sc10x.fmst) <- "pops"
Idents(sc10x.st) <- "pops"
Idents(sc10x.leu) <- "leu"

plot <- DimPlot(sc10x,reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")
postscript(paste0("./analysis/vis/singler/UMAP_all.eps"))
print(plot)
dev.off()

for (i in c("epi","fmst","st","leu")){
  plot <- DimPlot(get(paste0("sc10x.",i)),reduction="umap",label=TRUE,repel=TRUE)+theme(legend.position="none")
  postscript(paste0("./analysis/vis/singler/UMAP_",i,".eps"))
  print(plot)
  dev.off()
}

rm(list=ls(pattern="^sc10x.se"))

#scShinyOutput(sc10x,anal="id")
#scShinyOutput(sc10x.epi,anal="id.epi")
#scShinyOutput(sc10x.fmst,anal="id.fmst")
#scShinyOutput(sc10x.st,anal="id.st")
#scShinyOutput(sc10x.leu,anal="id.leu")

save(list=ls(pattern="^singler"),file='./analysis/singler_objects.RData')
save(list=ls(pattern="^sc10x"),file='./analysis/sc10x.id.rda')
save(list=ls(pattern="^sc10x.epi"),file='./analysis/sc10x.epi.id.rda')
save(list=ls(pattern="^sc10x.st"),file='./analysis/sc10x.st.id.rda')
#save.image(file="./analysis/sc10x.id.RData")