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