spatGenePlot

Visualize cells and gene expression according to spatial coordinates

spatGenePlot(...)

Arguments

...

Arguments passed on to spatGenePlot2D

gobject: giotto object
show_image: show a tissue background image
gimage: a giotto image
image_name: name of a giotto image
sdimx: x-axis dimension name (default = 'sdimx')
sdimy: y-axis dimension name (default = 'sdimy')
expression_values: gene expression values to use
genes: genes to show
cell_color_gradient: vector with 3 colors for numeric data
gradient_midpoint: midpoint for color gradient
gradient_limits: vector with lower and upper limits
show_network: show underlying spatial network
network_color: color of spatial network
spatial_network_name: name of spatial network to use
edge_alpha: alpha of edge
show_grid: show spatial grid
grid_color: color of spatial grid
spatial_grid_name: name of spatial grid to use
midpoint: expression midpoint
scale_alpha_with_expression: scale expression with ggplot alpha parameter
point_shape: shape of points (border, no_border or voronoi)
point_size: size of point (cell)
point_alpha: transparancy of points
point_border_col: color of border around points
point_border_stroke: stroke size of border around points
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_legend: show legend
legend_text: size of legend text
background_color: color of plot background
vor_border_color: border colorr for voronoi plot
vor_max_radius: maximum radius for voronoi 'cells'
vor_alpha: transparancy of voronoi 'cells'
axis_text: size of axis text
axis_title: size of axis title
show_plot: show plots
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.

Examples


data(mini_giotto_single_cell)

all_genes = slot(mini_giotto_single_cell, 'gene_ID')
selected_genes = all_genes[1:2]
spatGenePlot(mini_giotto_single_cell, genes = selected_genes, point_size = 3)

Arguments

Value

Details

See also

Examples