knitr::opts_chunk$set(message = FALSE, warning = FALSE, error = TRUE)
library(ggcyto) dataDir <- system.file("extdata",package="flowWorkspaceData") gs <- load_gs(list.files(dataDir, pattern = "gs_manual",full = TRUE))
By specifying the dimensions through
aes and selecting the cell population through
ggcyto can easily visualize the gated data stored in
p <- ggcyto(gs, aes(x = CD4, y = CD8), subset = "CD3+") # 2d plot p <- p + geom_hex(bins = 64) p
We can use the instrument range to automatically filter out these outlier cell events
p + ggcyto_par_set(limits = "instrument")
Or by setting limits manually
myPars <- ggcyto_par_set(limits = list(x = c(0,3.5e3), y = c(-10, 4.1e3))) p <- p + myPars# or xlim(0,3.5e3) + ylim(-10, 4e3) p
To check what kind of visualization parameters can be changed through
ggcyto_par_set, simply print the default settings
To plot a gate, simply pass the gate name to the
p + geom_gate("CD4")
More than one gate can be added as long as they share the same parent and dimensions
p <- p + geom_gate(c("CD4","CD8")) # short for geom_gate("CD8") + geom_gate("CD4") p
By default, stats for all gate layers are added through empty
p + geom_stats() + labs_cyto("marker")
Note that we choose to only display marker on axis through
labs_cyto layer here.
To add stats just for one specific gate, we can pass the gate name to
p + geom_stats("CD4")
stats type, background color and position are all adjustable.
p + geom_stats("CD4", type = "count", size = 6, color = "white", fill = "black", adjust = 0.3)
When 'subset' is not specified, it is at abstract status thus can not be visualized
p <- ggcyto(gs, aes(x = CD4, y = CD8)) + geom_hex() + myPars p
unless it is instantiated by the gate layer, i.e. lookup the gating tree for the parent node based on the given gates in
p <- p + geom_gate(c("CD4", "CD8")) p
geom_overlay, you can easily overlay the additional cell populations (whose gates are not defined in the current projection) on top of the existing plot.
p + geom_overlay("CD8/CCR7- 45RA+", col = "black", size = 0.1, alpha = 0.4)
geom_overlay automatically determines the overlay type (
geom_density) based on the number of dimensions specified in
Note that we change the default
y axis from
count in order to make the scales comparable for the stacked density layers. They are wrapped with
.. because they belong to the
p <- ggcyto(gs, aes(x = CD4), subset = "CD3+") + geom_density(aes(y = ..count..)) p + geom_overlay("CD8/CCR7- 45RA+", aes(y = ..count..), fill = "red")
Alternatively, we can choose to plot all children of one specified parent and projections
p <- ggcyto(gs, aes(x = 38, y = DR), subset = "CD4") + geom_hex(bins = 64) + geom_gate() + geom_stats() p
Or we can add gate layer to any arbitary node instead of its parent node
ggcyto(gs, subset = "root", aes(x = CD4, y = CD8)) + geom_hex(bins = 64) + geom_gate("CD4") + myPars
Sometime it is helpful to display the axis label in raw scale by inverse transforming the axis without affecting the data
p + axis_x_inverse_trans() + axis_y_inverse_trans() #add filter (consistent with `margin` behavior in flowViz) # ggcyto(gs, aes(x = CD4, y = CD8), subset = "CD3+", filter = marginalFilter) + geom_hex(bins = 32, na.rm = T)
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