library(ggcyto)
data(GvHD)
fs <- GvHD[subset(pData(GvHD), Patient %in%5:7 & Visit %in% c(5:6))[["name"]]]
fr <- fs[[1]]

1d histogram/densityplot

ggcyto wrapper will construct the ggcyto object that inherits from ggplot class.

p <- ggcyto(fs, aes(x = `FSC-H`)) 
class(p)
## [1] "ggcyto_flowSet"
## attr(,"package")
## [1] "ggcyto"
is(p, "ggplot")
## [1] TRUE

Since only one dimension is specified, we can add any 1d geom layer

p1 <- p + geom_histogram() 
p1

As shown, data is facetted by samples name automatically (i.e facet_wrap(~name)).

We can overwrite the default faceting by any variables that are defined in pData

pData(fs)
##       Patient Visit Days Grade  name
## s5a05       5     5   19     3 s5a05
## s5a06       5     6   26     3 s5a06
## s6a05       6     5   19     3 s6a05
## s6a06       6     6   27     3 s6a06
## s7a05       7     5   21     3 s7a05
## s7a06       7     6   28     3 s7a06
p1 + facet_grid(Patient~Visit)

To display 1d density

p + geom_density()

Fill the same color

p + geom_density(fill = "black")

Fill different colors

ggcyto(fs, aes(x = `FSC-H`, fill = name)) + geom_density(alpha = 0.2)

Or plot in the same panel by using ggplot directly (thus removing the default facetting effect)

ggplot(fs, aes(x = `FSC-H`, fill = name)) + geom_density(alpha = 0.2)

2d scatter/dot plot

# 2d hex
p <- ggcyto(fs, aes(x = `FSC-H`, y =  `SSC-H`))
p <- p + geom_hex(bins = 128)
p

A default scale_fill_gradientn is applied to 2d hexbin plot.

To add limits

p <- p + ylim(c(10,9e2)) + xlim(c(10,9e2))   
p

To overwrite the default fill gradien

p + scale_fill_gradientn(colours = rainbow(7), trans = "sqrt")

p + scale_fill_gradient(trans = "sqrt", low = "gray", high = "black")

Add geom_gate and geom_stats layers

Firstly we create the polygonGate with a data-driven method provided by flowStats package.

# estimate a lymphGate
lg <- flowStats::lymphGate(fr, channels=c("FSC-H", "SSC-H"),scale=0.6)
norm.filter <- lg$n2gate
#fit norm2 filter to multiple samples
fres <- filter(fs, norm.filter)
#extract the polygonGate for each sample
poly.gates <- lapply(fres, function(res)flowViz:::norm2Polygon(filterDetails(res, "defaultLymphGate")))
poly.gates
## $s5a05
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H
## 
## $s5a06
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H
## 
## $s6a05
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H
## 
## $s6a06
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H
## 
## $s7a05
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H
## 
## $s7a06
## Polygonal gate 'defaultPolygonGate' with 50 vertices in dimensions FSC-H and SSC-H

Then pass the gates to the gate layer

p + geom_gate(poly.gates)