flowBin: function to run the entire flowBin pipeline
In flowBin: Combining multitube flow cytometry data by binning

Description Usage Arguments Value Examples

Takes a list of flowFrames representing tubes from a single flow cytometry sample, and combines them using binning of events in terms of common markers across tubes.

  flowBin(tube.list, bin.pars, control.tubes = vector(),
    measure.pars = NULL,
    sample.name = "Unnamed Flow Expr Set",
    bin.method = "kmeans", expr.method = "medianFI",
    sparse.bin.thresh = 0.001, dequantize = T,
    snow.cluster = NULL, n.bins = 128, scale.expr = F,
    do.qnorm = T, return.bins = F)

`tube.list`	a list of flowFrames, one for each tube to combine
`bin.pars`	a numerical vector indicating which flow parameters in the each flowFrame to use for combining tubes. These should be the same markers assayed across every tube.
`control.tubes`	a vector indicating which tubes in tube.list to use for negative controls. May be empty.
`measure.pars`	a list of which parameters to measure expression for, with one vector for each tube. If left NULL, this defaults to all parameters other than those specified as `bin.pars`
`sample.name`	name of this flowSample, for convenience (defaults to 'Unnamed Flow Expr Set')
`bin.method`	The method to use for creating bins. The two options are "kmeans" for k-means clustering and nearest-neighbour mapping of bins. or "flowFP" for flowFP binning and direct mapping of bin boundaries across tubes.
`expr.method`	The method to use to compute bin expression across tubes. This defaults to MFI of the cells belonging to that bin in each tube. Other options are
`sparse.bin.thresh`	Bins which contain fewer than this proportion of total events in any tube will be excluded as outliers. Defaults to 0.001
`dequantize`	If TRUE, adds a small (region of 1e-8) value to flow data to help break ties when binning.
`snow.cluster`	A cluster created using the `snow` package, which flowBin will use to speed up computation. If NULL, flowBin will execute in serial mode.
`n.bins`	Number of bins to use. Note that this must be a power of 2 if flowFP is selected as binning method.
`scale.expr`	If TRUE, the resulting expression values will be scaled to (0,1) using the ranges specified in the flowFrames in `tube.list`.
`do.qnorm`	If TRUE, the binning markers will be quantile normalized prior to binning.
`return.bins`	If TRUE, return a `BinnedFlowExprSet` containing the bins themselves as well as the expression for each bin.

A matrix containing expression values for each bin in terms of each marker across all tubes. If return.bins is set TRUE, then a list containing a BinnedFlowExprSet followed by the expression matrix is returned.

data(amlsample)
tube.combined <- flowBin(aml.sample@tube.set,
bin.pars=aml.sample@bin.pars, 
bin.method='flowFP',
control.tubes=aml.sample@control.tubes, 
expr.method='medianFIDist', scale.expr=TRUE)
heatmap(tube.combined, scale='none')