plotRankSpatvsExpr

Plots dotplot to compare ligand-receptor rankings from spatial and expression information

plotRankSpatvsExpr(
  gobject,
  combCC,
  expr_rnk_column = "LR_expr_rnk",
  spat_rnk_column = "LR_spat_rnk",
  dot_color_gradient = NULL,
  midpoint = deprecated(),
  gradient_midpoint = 10,
  gradient_style = c("divergent", "sequential"),
  size_range = c(0.01, 1.5),
  xlims = NULL,
  ylims = NULL,
  selected_ranks = c(1, 10, 20),
  show_plot = NULL,
  return_plot = NULL,
  save_plot = NULL,
  save_param = list(),
  default_save_name = "plotRankSpatvsExpr"
)

Arguments

gobject

giotto object

combCC

combined communication scores from combCCcom

expr_rnk_column

column with expression rank information to use

spat_rnk_column

column with spatial rank information to use

dot_color_gradient

character. continuous colors to use. palette to use or vector of colors to use (minimum of 2).

midpoint

deprecated

gradient_midpoint

numeric. default = 10. midpoint of colors

gradient_style

either 'divergent' (midpoint is used in color scaling) or 'sequential' (scaled based on data range)

size_range

size ranges of dotplot

xlims

x-limits, numerical vector of 2

ylims

y-limits, numerical vector of 2

selected_ranks

numerical vector, will be used to print out the percentage of top spatial ranks are recovered

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

default_save_name

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

Value

ggplot

Examples

g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap 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"

exprCC <- exprCellCellcom(g,
    cluster_column = "leiden_clus",
    feat_set_1 = "Gm19935", feat_set_2 = "9630013A20Rik"
)
spatialCC <- spatCellCellcom(
    gobject = g, cluster_column = "leiden_clus",
    feat_set_1 = "Gm19935", feat_set_2 = "9630013A20Rik", verbose = "a lot",
    random_iter = 10
)
#> Error: package 'future' is not yet installed
#> 
#>  To install:
#> install.packages(c("future"))

combCC <- combCCcom(spatialCC = spatialCC, exprCC = exprCC)
#> Error: object 'spatialCC' not found

plotRankSpatvsExpr(gobject = g, combCC = combCC)
#> Error: object 'combCC' not found