Render a stylable heatmap of count data based on celda clustering results.
celdaHeatmap( sce, useAssay = "counts", altExpName = "featureSubset", featureIx = NULL, nfeatures = 25, ... ) # S4 method for SingleCellExperiment celdaHeatmap( sce, useAssay = "counts", altExpName = "featureSubset", featureIx = NULL, nfeatures = 25, ... )
sce | A SingleCellExperiment object returned by celda_C, celda_G, or celda_CG. |
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useAssay | A string specifying which assay slot to use. Default "counts". |
altExpName | The name for the altExp slot to use. Default "featureSubset". |
featureIx | Integer vector. Select features for display in heatmap. If
NULL, no subsetting will be performed. Default NULL. Only used for
|
nfeatures | Integer. Maximum number of features to select for each
gene module. Default 25. Only used for |
... | Additional parameters passed to plotHeatmap. |
list A list containing dendrogram information and the heatmap grob
`celdaTsne()` for generating 2-dimensional tSNE coordinates
#> TableGrob (5 x 6) "layout": 9 grobs #> z cells name grob #> 1 1 (2-2,3-3) col_tree polyline[GRID.polyline.16] #> 2 2 (4-4,1-1) row_tree polyline[GRID.polyline.17] #> 3 3 (4-4,3-3) matrix gTree[GRID.gTree.19] #> 4 4 (3-3,3-3) col_annotation rect[GRID.rect.20] #> 5 5 (3-3,4-4) col_annotation_names text[GRID.text.21] #> 6 6 (4-4,2-2) row_annotation rect[GRID.rect.22] #> 7 7 (5-5,2-2) row_annotation_names text[GRID.text.23] #> 8 8 (4-5,6-6) annotationLegend gTree[GRID.gTree.31] #> 9 9 (4-5,5-5) legend gTree[GRID.gTree.34]