Visualize cells according to dimension reduction coordinates

dimCellPlot2D(
  gobject,
  dim_reduction_to_use = "umap",
  dim_reduction_name = "umap",
  dim1_to_use = 1,
  dim2_to_use = 2,
  spat_enr_names = NULL,
  cell_annotation_values = NULL,
  show_NN_network = F,
  nn_network_to_use = "sNN",
  network_name = "sNN.pca",
  cell_color_code = NULL,
  cell_color_gradient = c("blue", "white", "red"),
  gradient_midpoint = NULL,
  gradient_limits = NULL,
  select_cell_groups = NULL,
  select_cells = NULL,
  show_other_cells = T,
  other_cell_color = "lightgrey",
  other_point_size = 0.5,
  show_cluster_center = F,
  show_center_label = T,
  center_point_size = 4,
  center_point_border_col = "black",
  center_point_border_stroke = 0.1,
  label_size = 4,
  label_fontface = "bold",
  edge_alpha = NULL,
  point_shape = c("border", "no_border"),
  point_size = 1,
  point_alpha = 1,
  point_border_col = "black",
  point_border_stroke = 0.1,
  show_legend = T,
  legend_text = 8,
  legend_symbol_size = 1,
  background_color = "white",
  axis_text = 8,
  axis_title = 8,
  cow_n_col = 2,
  cow_rel_h = 1,
  cow_rel_w = 1,
  cow_align = "h",
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "dimCellPlot2D"
)

Arguments

gobject

giotto object

dim_reduction_to_use

dimension reduction to use

dim_reduction_name

dimension reduction name

dim1_to_use

dimension to use on x-axis

dim2_to_use

dimension to use on y-axis

spat_enr_names

names of spatial enrichment results to include

cell_annotation_values

numeric cell annotation columns

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

cell_color_code

named vector with colors for cell annotation values

cell_color_gradient

vector with 3 colors for numeric data

gradient_midpoint

midpoint for color gradient

gradient_limits

vector with lower and upper limits

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_cluster_center

plot center of selected clusters

show_center_label

plot label of selected clusters

center_point_size

size of center points

center_point_border_col

border color of center points

center_point_border_stroke

border stroke size of center points

label_size

size of labels

label_fontface

font of labels

edge_alpha

column to use for alpha of the edges

point_shape

point with border or not (border or no_border)

point_size

size of point (cell)

point_alpha

transparancy of dim. reduction points

point_border_col

color of border around points

point_border_stroke

stroke size of border around points

show_legend

show legend

legend_text

size of legend text

legend_symbol_size

size of legend symbols

background_color

color of plot background

axis_text

size of axis text

axis_title

size of axis title

cow_n_col

cowplot param: how many columns

cow_rel_h

cowplot param: relative height

cow_rel_w

cowplot param: relative width

cow_align

cowplot param: how to align

show_plot

show plot

return_plot

return ggplot object

save_plot

directly save the plot [boolean]

save_param

list of saving parameters, see showSaveParameters

default_save_name

default save name for saving, don't change, change save_name in save_param

Value

ggplot

Details

Description of parameters. For 3D plots see dimPlot3D

See also

Other dimension reduction cell annotation visualizations: dimCellPlot()

Examples


data(mini_giotto_single_cell)

# combine all metadata
combineMetadata(mini_giotto_single_cell, spat_enr_names = 'cluster_metagene')

# visualize total expression information
dimCellPlot2D(mini_giotto_single_cell, cell_annotation_values = 'total_expr')

# visualize enrichment results
dimCellPlot2D(mini_giotto_single_cell,
               spat_enr_names = 'cluster_metagene',
               cell_annotation_values = c('1','2'))