Visualize Cells By Dimension Reduction Coordinates in 3D¶

plotTSNE_3D()

Visualize cells according to dimension reduction coordinates.

plotTSNE_3D(
    gobject,
    dim_reduction_name = "tsne",
    default_save_name = "TSNE_3D",
    ...
)

Arguments¶

gobject	giotto object
dim_reduction_name	name of TSNE
default_save_name	default save name of TSNE plot
…	Arguments passed on to dimPlot3D()
dim1_to_use	dimension to use on x-axis
dim2_to_use	dimension to use on y-axis
dim3_to_use	dimension to use on z-axis
spat_enr_names	names of spatial enrichment results to include
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 of not selected cells
other_point_size	size of not selected cells
show_NN_network	show underlying NN network
nn_network_to_use	type of NN network to use (kNN vs sNN)
network_name	name of NN network to use, if show_NN_network = TRUE
color_as_factor	convert color column to factor
cell_color	color for cells (see details)
cell_color_code	named vector with colors
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)
show_plot	show plot
return_plot	return ggplot object
save_plot	directly save the plot [boolean]
save_param	list of saving parameters, see showSaveParameters()

Value¶

A plotly.

Details¶

This is a wrapper function for tSNE 3D visualization. tSNE can accept as input the original gene expression matrix (set dim_reduction_to_use=NULL) or the dimension reduced matrix from PCA (default) (dim_reduction_to_use=”pca”). If principle components are analyzed, then one specifies the dimensions_to_use.

For tSNE, one can further define perplexity and theta options (see tSNE guide here). The options set_seed and seed_number are helpful to fix the random number generation seed so that the same result is returned each time the function is run.

A plot will be returned in the result.