Computes heatmap for a set of features against dimensionality reduction components

The computeHeatmap method computes the heatmap visualization for a set of features against a set of dimensionality reduction components. This method uses the heatmap computation algorithm code from Seurat but plots the heatmap using ComplexHeatmap and cowplot libraries.

computeHeatmap(
  inSCE,
  useAssay,
  dims = 10,
  nfeatures = 30,
  cells = NULL,
  reduction = "pca",
  disp.min = -2.5,
  disp.max = 2.5,
  balanced = TRUE,
  nCol = NULL,
  externalReduction = NULL
)

Arguments

inSCE

Input SingleCellExperiment object.

useAssay

Specify the name of the assay that will be scaled by this function for the features that are used in the heatmap.

dims

Specify the number of dimensions to use for heatmap. Default 10.

nfeatures

Specify the number of features to use for heatmap. Default is 30.

cells

Specify the samples/cells to use for heatmap computation. Default is NULL which will utilize all samples in the assay.

reduction

Specify the reduction slot in the input object. Default is "pca".

disp.min

Specify the minimum dispersion value to use for floor clipping of assay values. Default is -2.5.

disp.max

Specify the maximum dispersion value to use for ceiling clipping of assay values. Default is 2.5.

balanced

Specify if the number of of up-regulated and down-regulated features should be balanced. Default is TRUE.

nCol

Specify the number of columns in the output plot. Default is NULL which will auto-compute the number of columns.

externalReduction

Specify an external reduction if not present in the input object. This external reduction should be created using CreateDimReducObject function.

Value

Heatmap plot object.