histogram_vs_densityplot
In flowViz: Visualization for flow cytometry

library(knitr)
opts_chunk$set(message = FALSE, warning = FALSE)

library(flowViz)
data(GvHD)
fs <- GvHD[1:5]
fs <- transform(fs, estimateLogicle(fs[[1]], colnames(fs)[-c(1:2)]))

One sample(`flowFrame`) vs one channel

fr <- fs[[1]]
densityplot(~`FL1-H`, fr)
histogram(~`FL1-H`, fr)
histogram(~`FL1-H`, fr, breaks = 50) ##change the breaks

# change the border colors for hist
flowViz.par.set("superpose.polygon", list(border = "white"))
histogram(~`FL1-H`, fr, breaks = 50)

One sample vs multi-channels

densityplot(~., fr, channels = c("FL1-H", "FL2-H"))
histogram(~., fr, channels = c("FL1-H", "FL2-H"), breaks = 50)
densityplot(~., fr) #default will plot all channels
histogram(~., fr)
densityplot(~., fr, margin = F) #disable margin filtering
histogram(~., fr, margin = F)

Multi-samples (`flowSet`) vs one channel

densityplot(~`FL1-H`, fs)
histogram(~`FL1-H`, fs, breaks = 50)

#non-stacked version
densityplot(~`FL1-H`, fs, stack = F)
histogram(~`FL1-H`, fs, stack = F, breaks = 50, col = "white")

# change histogram type
histogram(~`FL1-H`, fs, stack = F, breaks = 50, col = "white", hist.type = "count")
histogram(~`FL1-H`, fs, stack = F, breaks = 50, col = "white", hist.type = "percent")
# Independent scales
histogram(~`FL1-H`, fs, stack = F, breaks = 50, col = "white", hist.type = "count"
          , scale = list(y=list(relation = "free")))

Multi-samples (`flowSet`) vs multi-channels

densityplot(~., fs, channels = c("FL1-H", "FL2-H"))
histogram(~., fs, channels = c("FL1-H", "FL2-H"), breaks = 50)

densityplot(~., fs)
histogram(~., fs, breaks = 50)

display gate

g <- rectangleGate(`FL1-H` =  c(3, 5))
densityplot(~`FL1`, fs, filter = g, stats = T)
densityplot(~`FL1`, fs, filter = g, stats = T, fitGate = F)#disable fitGate

histogram(~`FL1`, fs, stack = T, breaks = 1e2, type = "count", filter = g, stats = T)
histogram(~`FL1`, fs, stack = F, breaks = 1e2, type = "count", filter = g, stats = T)

`densityplot` + `overlay`

pos <- Subset(fs, g)
pos #gated population
#dispaly pos as overlay
xyplot(`FSC-H`~`FL1`, fs,overlay = list(pos = pos), xbin = 32, smooth = F)
# Not sure how to make y scale of the overlay to be compariable to the original density since its density is estimated indenpendenly.
densityplot(~`FL1`, fs, margin = F, overlay = list(pos =  pos), stack = F, filter = g, fitGate = F) 

# add overlay + independent y scaling
histogram(~`FL1`, fs, stack = F, breaks = 1e2, type = "count", filter = g, stats = T,overlay = list(pos =pos), scale = list(y=list(relation = "free")))