FlowSOM (version 1.0.0)

PlotPies: Plot comparison with other clustering

Description

Plot FlowSOM grid or tree, with pies indicating another clustering or manual gating result

Usage

PlotPies(fsom, cellTypes, MST=TRUE, legend=TRUE, clusters=NULL,main="", colorPalette=colorRampPalette(c("white","#00007F", "blue",  "#007FFF","cyan", "#7FFF7F", "yellow", "#FF7F00", "red")))

Arguments

fsom

FlowSOM object, as generated by BuildMST

cellTypes

Array of factors indicating the celltypes

MST

logical. If TRUE, plot tree, else plot grid

legend

logical. Sometimes the position of the legend is not great, so it might be easier to plot without

clusters

optional, clustering of the SOM nodes

main

Title of the plot

colorPalette

Color palette to use

Value

by a pie chart indicating the percentage of cells present of each cell type

See Also

PlotStars,PlotMarker,PlotCenters, BuildMST

Examples

    # Read from file, build self-organizing map and minimal spanning tree
    fileName <- system.file("extdata","lymphocytes.fcs",package="FlowSOM")
    flowSOM.res <- ReadInput(fileName, compensate=TRUE,transform=TRUE,
                            scale=TRUE)
    flowSOM.res <- BuildSOM(flowSOM.res,colsToUse=c(9,12,14:18))
    flowSOM.res <- BuildMST(flowSOM.res)
    
    # Get the manually gated labels using a gatingML file 
    # and the flowUtils library
    ff <- read.FCS(fileName)
    ff_c <- compensate(ff,ff@description$SPILL)
    colnames(ff_c)[8:18] <- paste("Comp-",colnames(ff_c)[8:18],sep="")
    library(flowUtils)
    flowEnv <- new.env()
    gatingFile <- system.file("extdata","manualGating.xml", 
                            package="FlowSOM")
    read.gatingML(gatingFile, flowEnv) 
    filterList <- list( "B cells" = flowEnv$ID52300206,
                    "ab T cells" = flowEnv$ID785879196,
                    "yd T cells" = flowEnv$ID188379411,
                    "NK cells" = flowEnv$ID1229333490,
                    "NKT cells" = flowEnv$ID275096433
                    )
    results <- list()
    for(cellType in names(filterList)){
        results[[cellType]] <- filter(ff_c,filterList[[cellType]])@subSet
    }
    manual <- rep("Unknown",nrow(ff))
    for(celltype in names(results)){
        manual[results[[celltype]]] <- celltype
    }
    
    # Plot pies indicating the percentage of cell types present in the nodes
    PlotPies(flowSOM.res,manual)