There may be a problem with the lymphGate plot function and potentially the entire function. While generating the lymphGate, the plot=TRUE option shows the correct population is selected. However, when using the non-Data() plotting technique after to show the populations (as demonstrated in '...A typical workflow'), the wrong population is shown. Here is an example: lymphfilter <- lymphGate(Data(wf[["biexponential"]]), channels=c("FSC.A", "SSC.A"), preselection="APC.H7.A", filterId="Lymphs", plot=TRUE, <- CORRECT POPULATION SHOWN scale=1.8) add(wf, lymphfilter$n2gate, parent="biexponential") Then: xyplot(`FSC.A` ~ `SSC.A` | Filename, wf[['Lymphs+']]) Shows the wrong population. Yet, with the 'usual' Data() plotting method the correct population is shown as within the gate: xyplot(`FSC.A` ~ `SSC.A` | Filename, Data(wf[['biexponential']]), nbin=c(400,400), filter=lymphfilter$n2gate) Interestingly, changing the above plot to smooth=FALSE results in the wrong population being highlighted once again: xyplot(`FSC.A` ~ `SSC.A` | Filename, Data(wf[['biexponential']]), smooth=FALSE, filter=lymphfilter$n2gate) However, I have question that the correct population is gated. Based upon the medians of each population it seems that the wrong population may have been chosen, I'm not sure how to really know for sure. median(exprs(Data(wf[["Lymphs-"]])[[2,"FSC.A"]])) [1] 59620.83 > median(exprs(Data(wf[["Lymphs+"]])[[2,"FSC.A"]])) [1] 35668.27 > median(exprs(Data(wf[["Lymphs+"]])[[1,"FSC.A"]])) [1] 34982.41 > median(exprs(Data(wf[["Lymphs-"]])[[1,"FSC.A"]])) [1] 62609.93 Anyone else seeing this? Thanks, Aric sessionInfo() R version 2.11.0 (2010-04-22) amd64-portbld-freebsd8.1 locale: [1] C attached base packages: [1] grid tools splines stats graphics grDevices utils [8] datasets methods base other attached packages: [1] Rgraphviz_1.26.0 graph_1.26.0 flowQ_1.9.0 [4] latticeExtra_0.6-11 RColorBrewer_1.0-2 parody_1.6.0 [7] bioDist_1.20.0 KernSmooth_2.23-3 outliers_0.13-2 [10] flowStats_1.7.5 cluster_1.12.3 mvoutlier_1.4 [13] fda_2.2.2 zoo_1.6-4 flowViz_1.13.1 [16] lattice_0.18-5 flowCore_1.15.2 rrcov_1.0-01 [19] pcaPP_1.8-2 mvtnorm_0.9-92 robustbase_0.5-0-1 [22] Biobase_2.8.0 fortunes_1.3-7 loaded via a namespace (and not attached): [1] AnnotationDbi_1.10.2 DBI_0.2-5 MASS_7.3-5 [4] RSQLite_0.9-2 annotate_1.26.1 feature_1.2.4 [7] geneplotter_1.26.0 ks_1.6.13 stats4_2.11.0 [10] tcltk_2.11.0 xtable_1.5-6

I believe this is just a plotting problem. The positive population in the workFlow appears to be the correct one, despite the median values. Carrying-on through many iterations of the plots confirms this. thanks, Aric