flowBin {flowBin} | R Documentation |
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 |
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
|
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 |
do.qnorm |
If TRUE, the binning markers will be quantile normalized prior to binning. |
return.bins |
If TRUE, return a
|
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')