ggcyto : Visualize Cytometry data with ggplot

Overloaded fortify S3 method makes Cytometry data to be fully compatible with ggplot.

library(ggcyto)
dataDir <- system.file("extdata",package="flowWorkspaceData")
gs <- load_gs(list.files(dataDir, pattern = "gs_manual",full = TRUE))
fs <- getData(gs, "CD3+")

Quick plot with autoplot

#1d
autoplot(fs, "CD4")

#2d
autoplot(fs, "CD4", "CD8", bins = 64)

autoplot(gs, c("CD4", "CD8"), bins = 64)

More flexibility with ggcyto wrapper

ggcyto + flowSet

# support fuzzy-matching of aes to the data
# with flowJo-type of default color fills
# facet on `name` by default
ggcyto(fs,aes(x = CD4, y = CD8)) + geom_hex(bins = 64) + xlim(0, 3600)

ggcyto + GatingSet

ggcyto(gs,aes(x = CCR7, y = CD45RA), subset = "CD4") + geom_hex(bins = 64) + geom_gate("CD4/CCR7+ 45RA+") + geom_stats(fill = "yellow", size = 4)

Use ggplot directly to have more controls.

# 1d
p <- ggplot(fs, aes(x = `<B710-A>`)) + facet_wrap(~name) 
#histogram plot
p + geom_histogram(colour = "white")

#density plot
p + geom_density(fill = "black")

# 2d hexbin
ggplot(fs, aes(x = `<B710-A>`, y = `<R780-A>`)) + facet_wrap(~name) + geom_hex(bins = 64)

More examples of using ggplot directly on flowSet:

• ggplot + flowSet1d
• ggplot + flowSet2d
• ggplot + flowSet + gate
• ggplot + flowSet + overlay