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

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

runSeuratHeatmap(
  inSCE,
  useAssay,
  useReduction = c("pca", "ica"),
  dims = NULL,
  nfeatures = 30,
  cells = NULL,
  ncol = NULL,
  balanced = TRUE,
  fast = TRUE,
  combine = TRUE,
  raster = TRUE,
  externalReduction = NULL
)

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

Number of features to include in the heatmap. Default 30.

cells

Numeric value indicating the number of top cells to plot. Default is NULL which indicates all cells.

ncol

Numeric value indicating the number of columns to use for plot. Default is NULL which will automatically compute accordingly.

balanced

Plot equal number of genes with positive and negative scores. Default is TRUE.

fast

See DimHeatmap for more information. Default TRUE.

combine

See DimHeatmap for more information. Default TRUE.

raster

See DimHeatmap for more information. Default TRUE.

externalReduction

Pass DimReduc object if PCA/ICA computed through other libraries. Default NULL.

Value

plot object

Examples

data(scExample, package = "singleCellTK")
if (FALSE) {
sce <- runSeuratNormalizeData(sce, useAssay = "counts")
sce <- runSeuratFindHVG(sce, useAssay = "counts")
sce <- runSeuratScaleData(sce, useAssay = "counts")
sce <- runSeuratPCA(sce, useAssay = "counts")
heatmap <- runSeuratHeatmap(sce, useAssay = "counts")
plotSeuratHeatmap(heatmap)
}