seuratRunUMAP: seuratRunUMAP Computes UMAP from the given sce object and...

In singleCellTK: Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Description

seuratRunUMAP Computes UMAP from the given sce object and stores the UMAP computations back into the sce object

Usage

seuratRunUMAP(
  inSCE,
  useReduction = c("pca", "ica"),
  reducedDimName = "seuratUMAP",
  dims = 10,
  minDist = 0.3,
  nNeighbors = 30L,
  spread = 1
)

Arguments

inSCE	(sce) object on which to compute the UMAP
useReduction	Reduction to use for computing UMAP. One of "pca" or "ica". Default is "pca".
reducedDimName	Name of new reducedDims object containing Seurat UMAP Default seuratUMAP.
dims	Numerical value of how many reduction components to use for UMAP computation. Default 10.
minDist	Sets the "min.dist" parameter to the underlying UMAP call. See RunUMAP for more information. Default 0.3.
nNeighbors	Sets the "n.neighbors" parameter to the underlying UMAP call. See RunUMAP for more information. Default 30L.
spread	Sets the "spread" parameter to the underlying UMAP call. See RunUMAP for more information. Default 1.

Value

Updated sce object with UMAP computations stored

Examples

data(scExample, package = "singleCellTK")
## Not run: 
sce <- seuratNormalizeData(sce, useAssay = "counts")
sce <- seuratFindHVG(sce, useAssay = "counts")
sce <- seuratScaleData(sce, useAssay = "counts")
sce <- seuratPCA(sce, useAssay = "counts")
sce <- seuratFindClusters(sce, useAssay = "counts")
sce <- seuratRunUMAP(sce, useReduction = "pca")

## End(Not run)

singleCellTK documentation built on Nov. 8, 2020, 5:21 p.m.