R/scanpyFunctions.R
runScanpyTSNE.Rd
runScanpyTSNE Computes tSNE from the given sce object and stores the tSNE computations back into the sce object
runScanpyTSNE(
inSCE,
useAssay = NULL,
useReducedDim = "scanpyPCA",
reducedDimName = "scanpyTSNE",
dims = 40,
perplexity = 30,
externalReduction = NULL,
seed = 12345
)
(sce) object on which to compute the tSNE
Specify name of assay to use. Default is NULL
, so
useReducedDim
param will be used instead.
selected reduction method to use for computing tSNE.
Default "scanpyPCA"
.
Name of new reducedDims object containing Scanpy tSNE
Default scanpyTSNE
.
Number of reduction components to use for tSNE computation.
Default 40
.
Adjust the perplexity tuneable parameter for the underlying
tSNE call. Default 30
.
Pass DimReduc object if PCA computed through
other libraries. Default NULL
.
Specify numeric value to set as a seed. Default 12345
.
Updated sce object with tSNE computations stored
data(scExample, package = "singleCellTK")
if (FALSE) {
sce <- runScanpyNormalizeData(sce, useAssay = "counts")
sce <- runScanpyFindHVG(sce, useAssay = "scanpyNormData", method = "seurat")
sce <- runScanpyScaleData(sce, useAssay = "scanpyNormData")
sce <- runScanpyPCA(sce, useAssay = "scanpyScaledData")
sce <- runScanpyFindClusters(sce, useReducedDim = "scanpyPCA")
sce <- runScanpyTSNE(sce, useReducedDim = "scanpyPCA")
}