Plots recovery plot to compare ligand-receptor rankings from spatial and expression information
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
- ground_truth
what to consider as ground truth (default: spatial)
- 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
#> cell_spatInfo_spatVector.shp
#> cell
#>
#> 3.2 read Giotto spatial centroid information
#> cell
#>
#> 3.3 read Giotto spatial overlap information
#> No overlaps were found, overlap loading will be
#> skipped
#>
#> 4. read Giotto image information
#> a giotto python environment was found
#> Using python path:
#> "/Users/yuanlab/Library/r-miniconda/envs/giotto_env/bin/pythonw"
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)
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10 <- Inf returned
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10
#> simulations: 1 2 3 4 5 6 7 8 9 10 <- Inf returned
#> Warning: no adjusted p.values that are not zero; returning Inf
#> Warning: no adjusted p.values that are not zero; returning Inf
combCC <- combCCcom(spatialCC = spatialCC, exprCC = exprCC)
plotRecovery(gobject = g, combCC = combCC)
#> percentage explained = NaN
#> Warning: Removed 29 rows containing missing values or values outside the scale range
#> (`geom_point()`).
