glpoints-methods: Adding points within a gate to a plot
In flowViz: Visualization for flow cytometry

Description Usage Arguments Details Methods Author(s) See Also

These methods extend the lattice lpoints methods for drawing of points contained within a filter. They allow for multiple dispatch, since not all filter types need to be evaluated for plotting, but this decision should be made internally. In any case, we need the raw data in the form of a flowFrame.

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## S4 method for signature 'filter,flowFrame,missing'
glpoints(x, data, channels,
  verbose = TRUE, filterResult = NULL, ...)

`x`	filter, filterResult or any derived filter class
`data`	flowFrame or missing
`channels`	character or missing
`verbose`	logical
`filterResult`	filterResult class
`...`	other arguments

When plotting flowFrames using the plot method provided by flowViz, the plotted parameters are recorded, which makes it possible to correctly overlay the points within filters assuming that they are defined for the respective parameters. Warnings and error will be cast for the cases where the parameters are non-distinct or ambigious. These methods are meant to be used within lattice panel functions and are probably not of much use outside of those.

x = "filter", data = "flowFrame", channels = "missing": General method for all objects inheriting from filter. This is used as the default when no more explicit method is found. It tries to find the plotted parameters from the internal flowViz.state environment. This only works if the flow data has been plotted using the plot methods provided by this flowViz package.
x = "filter", data = "missing", channels = "ANY": This gives a useful error message when we don't get what we need.
x = "filterResult", data = "flowFrame", channels =: We can get all the information about a filter from its filterResult without the need to re-evaluate.
"character": We can get all the information about a filter from its filterResult without the need to re-evaluate.
x = "curv1Filter", data = "ANY": We either need a filterResult or the raw data as a flowFrame for curv1Filters.
x = "curv1Filter", data = "flowFrame": see above
x = "curv1Filter", data = "missing": see above
x = "curv1Filter", data = "multipleFilterResult": see above
x = "curv2Filter", data = "ANY": We either need a filterResult or the raw data as a flowFrame for curv2Filters.
x = "curv1Filter", data = "flowFrame", channels =: We evaluate the filter on the flowFrame and plot the subset of selected points. By default, every subpopulation (if there are any) is colored differently.
"character": We evaluate the filter on the flowFrame and plot the subset of selected points. By default, every subpopulation (if there are any) is colored differently.
x = "curv2Filter", data = "flowFrame", channels = "character": see above
x = "kmeansFilter", data = "flowFrame", channels =: see above
"character": see above
x = "norm2Filter", data = "flowFrame", channels =: see above
"character": see above
x = "polygonGate", data = "flowFrame", channels =: see above
"character": see above
x = "quadGate", data = "flowFrame", channels = "character": see above
x = "rectangleGate", data = "flowFrame", channels =: see above
"character": see above
x = "ellipsoidGate", data = "flowFrame", channels =: see above
"character": see above