For this type of two-mode distributions, you can try one of the 2d gating function (flowClust.2d) provided by openCyto package to gate out one population and then use the negate gate for the other. Here is one reproducible example to get CD3+ and CD3-
library(openCyto) #load the gated data dataDir <- system.file("extdata",package="flowWorkspaceData") gs <- load_gs(list.files(dataDir, pattern = "gs_manual",full = TRUE)) #get the parent data fs <- getData(gs, "singlets") fr <- fs[] #get the first sample # run 2d gating to get CD3+ gate g <- flowClust.2d(fr, xChannel = "SSC-A", yChannel = "<V450-A>" ) #visualize it xyplot(`SSC-A`~`CD3`, fr, xbin = 32, smooth = F, stats = T, filter = g)
On 03/11/2015 08:44 AM, Jill M Trivedi wrote:
I have this flow cytometry data that I am attempting to analyze with flowStats. However, I am finding it difficult to find a gating function that recognizes the two populations based on density. Is there any particular gate you would recommend to do this? or a combination of gates?