Description Usage Arguments Details Value
The low power and high noise in some analyses makes it necessary to bind multiple samples together. Given an SPExp object, this method separates out each cell type, calculate neighbour means and binds the samples together, i.e. the individual response matrices for different samples Y1, Y2, Y3 are rowbound together to form one large response matrix Y = [Y1' Y2' Y3']'.
1 
SPE 
The SPExp object to use 
choose.class 
Choose a particular class of cells. Should be a vector of length

use.weights 
Passed to neighbourMeans to optionally weight the regression by relative boundary size 
normalize 
If true predictor columns are centrescaled 
If normalize = TRUE
it is necessary to introduce sample factors as constructed
by ConstructSampleFactors
, otherwise the regression estimates will be affected
by the relative means of different samples.
A list with three components:
X
The bound predictor matrix
Y
The bound response matrix
sizes
A vector with the number of cells selected from each SPE
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