flowBin: function to run the entire flowBin pipeline

Description

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.

Usage

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)

Arguments

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.

Value

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.

Examples

Run this code

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')

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