GLMPCA | R Documentation |
This function implements the GLM-PCA dimensionality reduction
method for high-dimensional count data. This is a wrapper for
glmpca
.
GLMPCA(object, ...) ## S4 method for signature 'SummarizedExperiment' GLMPCA(object, L, assay = "counts", ...) ## S4 method for signature 'matrix' GLMPCA(object, L, ...) ## S4 method for signature 'Matrix' GLMPCA(object, L, ...)
object |
A |
... |
further arguments passed to |
L |
the desired number of latent dimensions (integer). |
assay |
a character or integer specifying which assay to use for GLM-PCA
(default = 'counts'). Ignored if |
The original SingleCellExperiment
or
SummarizedExperiment
object with the GLM-PCA results added to the
metadata
slot. If the original input was a
SingleCellExperiment
, then a new reducedDim
element called
"GLMPCA"
will be added, representing the GLM-PCA factors
. If
the input was a matrix, output matches that of
glmpca
.
ncells <- 100 u <- matrix(rpois(20000, 5), ncol=ncells) sce <- SingleCellExperiment::SingleCellExperiment(assays=list(counts=u)) GLMPCA(sce, L = 2)
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