Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework
Visualize spatial and clustering (dimensional reduction) data in a linked, interactive framework
LinkedDimPlot( object, dims = 1:2, reduction = NULL, image = NULL, group.by = NULL, alpha = c(0.1, 1), combine = TRUE ) LinkedFeaturePlot( object, feature, dims = 1:2, reduction = NULL, image = NULL, slot = "data", alpha = c(0.1, 1), combine = TRUE )
object |
Seurat object |
dims |
Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions |
reduction |
Which dimensionality reduction to use. If not specified, first searches for umap, then tsne, then pca |
image |
Name of the image to use in the plot |
group.by |
Name of one or more metadata columns to group (color) cells by (for example, orig.ident); pass 'ident' to group by identity class |
alpha |
Controls opacity of spots. Provide as a vector specifying the min and max |
combine |
Combine plots into a single |
feature |
Feature to visualize |
slot |
Which slot to pull expression data from? |
Returns final plots. If combine
, plots are stiched together
using CombinePlots
; otherwise, returns a list of ggplot objects
## Not run: LinkedDimPlot(seurat.object) LinkedFeaturePlot(seurat.object, feature = 'Hpca') ## End(Not run)
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