runDimReduce | R Documentation |
Generic Wrapper function for running dimensionality reduction
runDimReduce(
inSCE,
method = c("scaterPCA", "seuratPCA", "seuratICA", "scanpyPCA", "rTSNE", "seuratTSNE",
"scaterUMAP", "seuratUMAP", "scanpyUMAP", "scanpyTSNE"),
useAssay = NULL,
useReducedDim = NULL,
useAltExp = NULL,
reducedDimName = method,
nComponents = 20,
useFeatureSubset = NULL,
scale = FALSE,
seed = 12345,
...
)
inSCE |
Input SingleCellExperiment object. |
method |
One from |
useAssay |
Assay to use for computation. If |
useReducedDim |
The low dimension representation to use for embedding
computation. Default |
useAltExp |
The subset to use for computation, usually for the
selected variable features. Default |
reducedDimName |
The name of the result matrix. Required. |
nComponents |
Specify the number of dimensions to compute with the selected method in case of PCA/ICA and the number of components to use in the case of TSNE/UMAP methods. |
useFeatureSubset |
Subset of feature to use for dimension reduction. A
character string indicating a |
scale |
Logical scalar, whether to standardize the expression values.
Default |
seed |
Random seed for reproducibility of results.
Default |
... |
The other arguments for running a specific algorithm. Please refer to the one you use. |
Wrapper function to run one of the available dimensionality
reduction algorithms integrated within SCTK from scaterPCA
,
runSeuratPCA
, runSeuratICA
, runTSNE
,
runSeuratTSNE
, runUMAP
and
runSeuratUMAP
. Users can use an assay by specifying
useAssay
, use the assay in an altExp by specifying both
useAltExp
and useAssay
, or use a low-dimensionality
representation by specifying useReducedDim
.
The input SingleCellExperiment object with
reducedDim
updated with the result.
data(scExample, package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
sce <- runNormalization(sce, useAssay = "counts",
outAssayName = "logcounts",
normalizationMethod = "logNormCounts")
sce <- runDimReduce(inSCE = sce, method = "scaterPCA",
useAssay = "logcounts", scale = TRUE,
reducedDimName = "PCA")
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