seuratComputeHeatmap {singleCellTK} | R Documentation

## seuratComputeHeatmap Computes the heatmap plot object from the pca slot in the input sce object

### Description

seuratComputeHeatmap Computes the heatmap plot object from the pca slot in the input sce object

### Usage

    seuratComputeHeatmap(
      inSCE,
      useAssay,
      useReduction = c("pca", "ica"),
      dims = NULL,
      nfeatures = 30,
      fast = TRUE,
      combine = TRUE,
      raster = TRUE
    )

### Arguments

`inSCE` | (sce) object from which to compute heatmap (pca should be computed)
`useAssay` | Assay containing scaled counts to use in heatmap.
`useReduction` | Reduction method to use for computing clusters. One of "pca" or "ica". Default `"pca"`.
`dims` | Number of components to generate heatmap plot objects. If `NULL`, a heatmap will be generated for all components. Default `NULL`.
`nfeatures` | Numer of features to include in the heatmap. Default `30`.
`fast` | See DimHeatmap for more information. Default `TRUE`.
`combine` | See DimHeatmap for more information. Default `TRUE`.
`raster` | See DimHeatmap for more information. Default `TRUE`.

### Value

plot object

### 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")
    heatmap <- seuratComputeHeatmap(sce, useAssay = "counts")
    seuratHeatmapPlot(heatmap)

    ## End(Not run)

[Package singleCellTK version 2.0.0 Index]