# Plot cytometry data using the ggcyto API

Source: `R/AllClasses.R`, `R/ggcyto.R`, `R/ggcyto_GatingSet.R`, and 1 more
`ggcyto.Rd`

`ggcyto()` initializes a ggcyto object that inherits ggplot class. Similarly the + operator can be used to add layers to the existing ggcyto object.

    ggcyto(data = NULL, ...)

    # S3 method for GatingSet
    ggcyto(data, mapping, subset = "_parent_", ...)

    # S3 method for GatingSetList
    ggcyto(data, ...)

    # S3 method for GatingHierarchy
    ggcyto(data, ...)

    # S3 method for flowSet
    ggcyto(data, mapping, filter = NULL, max_nrow_to_plot = 50000, ...)

## Arguments

data | The data source. A core cytometry data structure. (flowSet, flowFrame, ncdfFlowSet, GatingSet or GatingHierarchy)
... | other arguments passed to specific methods
mapping | default list of aesthetic mappings (these can be colour, size, shape, line type -- see individual geom functions for more details)
subset | character that specifies the node path or node name in the case of GatingSet. Default is "_parent_", which will be substituted with the actual node name based on the geom_gate layer to be added later.
filter | a flowcore gate object or a function that takes a flowSet and channels as input and returns a data-dependent flowcore gate. The gate is used to filter the flow data before it is plotted.
max_nrow_to_plot | the maximum number of cells to be plotted. When the actual data exceeds it, The subsampling process will be triggered to speed up plotting. Default is 5e4. To turn off the subsampling, simply set it to a large enough number or Inf.

## Value

ggcyto object

## Details

To invoke `ggcyto`:

- `ggcyto(fs, aes(x, y, <other aesthetics>))`

## Examples

    data(GvHD)
    fs <- GvHD[1:3]
    #construct the `ggcyto` object (inherits from `ggplot` class)
    p <- ggcyto(fs, aes(x = `FSC-H`))
    p + geom_histogram()#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
    # display density/area
    p + geom_density()p + geom_area(stat = "density")
    # 2d scatter plot
    p <- ggcyto(fs, aes(x = `FSC-H`, y =  `SSC-H`))
    p + geom_hex(bins = 128)# do it programatically through aes_string and variables
    col1 <- "`FSC-H`" #note that the dimension names with special characters needs to be quoted by backticks
    col2 <- "`SSC-H`"
    ggcyto(fs, aes_string(col1,col2)) + geom_hex()
    ## More flowSet examples
    fs <- GvHD[subset(pData(GvHD), Patient %in%5:7 & Visit %in% c(5:6))[["name"]]]
    # 1d histogram/densityplot
    p <- ggcyto(fs, aes(x = `FSC-H`))
    #facet_wrap(~name)` is used automatically
    p1 <- p + geom_histogram()
    p1#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.#overwriting the default faceeting
    p1 + facet_grid(Patient~Visit)#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
    #display density
    p + geom_density()
    #you can use ggridges package to display stacked density plot
    require(ggridges)#> Loading required package: ggridges#stack by fcs file ('name')
    p + geom_density_ridges(aes(y = name)) + facet_null() #facet_null is used to remove the default facet_wrap (by 'name' column)#> Picking joint bandwidth of 16.4#or to stack by Visit and facet by patient
    p + geom_density_ridges(aes(y = Visit)) + facet_grid(~Patient)#> Picking joint bandwidth of 29.2#> Picking joint bandwidth of 12.1#> Picking joint bandwidth of 7.74
    # 2d scatter/dot plot
    p <- ggcyto(fs, aes(x = `FSC-H`, y =  `SSC-H`))
    p <- p + geom_hex(bins = 128)
    p
    ## GatingSet
    dataDir <- system.file("extdata",package="flowWorkspaceData")
    gs <- load_gs(list.files(dataDir, pattern = "gs_manual",full = TRUE))
    # 2d plot
    ggcyto(gs, aes(x = CD4, y = CD8), subset = "CD3+") + geom_hex(bins = 64)
    # 1d plot
    ggcyto(gs, aes(x = CD4), subset = "CD3+")  + geom_density()