View source: R/computeHeatmap.R
computeHeatmap | R Documentation |
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
)
inSCE |
Input |
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
|
nfeatures |
Specify the number of features to use for heatmap. Default
is |
cells |
Specify the samples/cells to use for heatmap computation.
Default is |
reduction |
Specify the reduction slot in the input object. Default
is |
disp.min |
Specify the minimum dispersion value to use for floor
clipping of assay values. Default is |
disp.max |
Specify the maximum dispersion value to use for ceiling
clipping of assay values. Default is |
balanced |
Specify if the number of of up-regulated and down-regulated
features should be balanced. Default is |
nCol |
Specify the number of columns in the output plot. Default
is |
externalReduction |
Specify an external reduction if not present in
the input object. This external reduction should be created
using |
Heatmap plot object.
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