seuratRunUMAP {singleCellTK} | R Documentation

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

### 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)

[Package singleCellTK version 2.0.0 Index]