Visualize cells according to dimension reduction coordinates
Arguments
- gobject
giotto object
- dim_reduction_name
name of UMAP
- default_save_name
default save name of UMAP plot
- ...
Arguments passed on to
dimPlot3D
spat_unit
spatial unit (e.g. "cell")
feat_type
feature type (e.g. "rna", "dna", "protein")
show_plot
logical. show plot
return_plot
logical. return ggplot object
save_plot
logical. save the plot
save_param
list of saving parameters, see
showSaveParameters
dim1_to_use
numeric. dimension to use on x-axis
dim2_to_use
numeric. dimension to use on y-axis
dim3_to_use
numeric. dimension to use on z-axis
show_NN_network
logical. Show underlying NN network
nn_network_to_use
character. type of NN network to use (kNN vs sNN)
network_name
character. name of NN network to use, if show_NN_network = TRUE
spat_enr_names
character. names of spatial enrichment results to include
cell_color
character. what to color cells by (e.g. metadata col or spatial enrichment col)
color_as_factor
logical. convert color column to factor. Discrete colors are used when this is TRUE. continuous colors when FALSE.
cell_color_code
character. discrete colors to use. palette to use or named vector of colors
select_cell_groups
select subset of cells/clusters based on cell_color parameter
select_cells
select subset of cells based on cell IDs
show_other_cells
display not selected cells
other_cell_color
color for not selected cells
other_point_size
point size for not selected cells
show_cluster_center
plot center of selected clusters
show_center_label
plot label of selected clusters
center_point_size
size of center points
label_size
size of labels
edge_alpha
column to use for alpha of the edges
point_size
size of point (cell)
See also
Other reduced dimension visualizations:
dimPlot2D()
,
plotPCA()
,
plotPCA_2D()
,
plotPCA_3D()
,
plotTSNE()
,
plotTSNE_2D()
,
plotTSNE_3D()
,
plotUMAP()
,
plotUMAP_2D()
Examples
g <- GiottoData::loadGiottoMini("starmap")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 4. read Giotto image information
#> python already initialized in this session
#> active environment : '/usr/bin/python3'
#> python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#> "/usr/bin/python3"
plotUMAP_3D(g, dim_reduction_name = "3D_umap")
#> create 3D plot