Cytometry -data analysis

Import data with R

i = "ID01_11_027_ACC2921_Tube_013.fcs"
file_full = paste0("C://Users/vht/Desktop/vhtran_data_dalia/mydf/TCyto/",i)
FCS = read.FCS(file_full)
colnames(FCS)[which(colnames(FCS)=="SSC-A")] <- "SSCA"
colnames(FCS)[which(colnames(FCS)=="FSC-A")] <- "FSCA"
colnames(FCS)[which(colnames(FCS)=="Pacific Orange-A")] <- "CD8"
colnames(FCS)[which(colnames(FCS)=="Pacific Blue-A")] <- "CD4"
colnames(FCS)[which(colnames(FCS)=="PE-Texas Red-A")] <- "CD45RA"
colnames(FCS)[which(colnames(FCS)== "APC-Cy7-A")] <- "CD27"
colnames(FCS)[which(colnames(FCS)=="PE-Cy7-A")] <- "CCR7"
colnames(FCS)[which(colnames(FCS)=="PE-Cy5-A")] <- "CD3"
colnames(FCS)[which(colnames(FCS)=="PE-A")] <- "GranzA"
colnames(FCS)[which(colnames(FCS)=="FITC-A")] <- "Perf"
colnames(FCS)[which(colnames(FCS)=="APC-A")] <- "CD28"
colnames(FCS)[which(colnames(FCS)=="Alexa Fluor 700-A")] <- "GranB"
library(ggcyto)
# Standardize data
biexp  <- biexponentialTransform("myTransform",w=10)
myTrans <-  transformList(c('CD8','CD4',"SSCA","FSCA","CD3","Perf",
                            "CD28","CD27","GranzA","CD45RA","CCR7","GranB"), biexp)
FCS1 = transform(FCS, myTrans)
# Data brut
p1 = autoplot(FCS,"CD4","CD8",bins = 360) + xlim(-100,10000) + ylim(-100,10000)
p1

p2 = ggcyto(FCS1, aes(x = CD4, y = CD8)) + geom_hex(bins = 128) 
#p2 + geom_gate("CD8")
outFile <- file.path("C://Users/vht/Desktop/FCS2.fcs")
## now write out into a file
write.FCS(FCS1, outFile)

[1] "C://Users/vht/Desktop/FCS2.fcs"

library(ncdfFlow)
file_full1 = "C://Users/vht/Desktop/FCS2.fcs"
fs1<-read.flowSet(file_full1)
p4 <- ggcyto(fs1, aes(x =CD4, y = CD8)) + geom_hex(bins = 128)
rect.g <- rectangleGate(list("CD4" =  c(17,20), "CD8" = c(12,20)))
rect.gates <- sapply(sampleNames(fs1), function(sn)rect.g)
p4 + geom_gate(rect.gates) + geom_stats() + annotate(geom = "text", x = 18, y = 14, label  = "CD4+", color = "red")

file_full1

[1] "C://Users/vht/Desktop/FCS2.fcs"

FCS21 = read.FCS(file_full1)
FCS2 <- (FCS21@exprs)
M1 = FCS2[,c("SSCA","FSCA","CD3","CD4","CD8")]
M2 = asin(M1/23.170)
 CD4 = M1[,"CD4"]
 CD8 = M1[,"CD8"]
dd <- rbind(data.frame(value = CD4, id = 'CD4'), data.frame(value = CD8, id = 'CD8'))
ggplot(dd, aes(x=value)) + 
  #geom_histogram(aes(y=..ndensity..)) + 
  geom_density(aes(colour = id, y = ..scaled..)) + ylab("ndensity")

 CD4 = M1[,"CD4"]
 CD8 = M1[,"CD8"]
dd <- rbind(data.frame(value = CD4, id = 'CD4'), data.frame(value = CD8, id = 'CD8'))
p1 = ggplot(dd, aes(x=value, fill=id)) + geom_histogram(alpha=0.4,bins=100, position="identity") + xlim(13, 21)
p1 + xlab("Fluororescence intensity")