It essentially reconstructs the entire ggcyto plot object based on the new data and the original mapping and layers recorded in the plot object.

e1 %+% e2

Arguments

e1

the ggcyto object

e2

the new cytometry data . It can be 'GatingSet' or 'flowSet'.

Value

the new ggcyto object

Examples

dataDir <- system.file("extdata",package="flowWorkspaceData") gs <- load_gs(list.files(dataDir, pattern = "gs_bcell_auto",full = TRUE)) gs1 <- gs[1] gs2 <- gs[2] #construct the ggcyto object for gs1 p <- ggcyto(gs1, aes(cd24, cd38)) + geom_hex(bins = 128) p <- p + geom_gate("Transitional") #add gate #customize the stats layer p <- p + geom_stats(type = "count", size = 6, color = "white", fill = "black", adjust = 0.3) #customize the layer p <- p + labs_cyto("channel") #customize the axis limits p <- p + ggcyto_par_set(limits = "instrument")
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.
#add another population as the overlay dots p <- p + geom_overlay("IgD-CD27-", col = "black", size = 1.2, alpha = 0.4) #hide the legend p <- p + guides(fill=FALSE) p
#replace the data with gs2 and see the same visual effect p %+% gs2
#> Scale for 'fill' is already present. Adding another scale for 'fill', which #> will replace the existing scale.
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.