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 row-bound 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 centre-scaled |
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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