Description Usage Arguments Value Examples
Creates a known spatial pattern for selected genes one-by-one and runs the different spatial gene detection tests
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | runPatternSimulation(
gobject,
pattern_name = "pattern",
pattern_cell_ids = NULL,
gene_names = NULL,
spatial_probs = c(0.5, 1),
reps = 2,
spatial_network_name = "kNN_network",
spat_methods = c("binSpect_single", "binSpect_multi", "spatialDE", "spark"),
spat_methods_params = list(NA, NA, NA, NA),
spat_methods_names = c("binSpect_single", "binSpect_multi", "spatialDE", "spark"),
save_plot = T,
save_raw = T,
save_norm = T,
save_dir = "~",
max_col = 4,
height = 7,
width = 7,
run_simulations = TRUE,
...
)
|
gobject |
giotto object |
pattern_name |
name of spatial pattern |
pattern_cell_ids |
cell ids that make up the spatial pattern |
gene_names |
selected genes |
spatial_probs |
probabilities to test for a high expressing gene value to be part of the spatial pattern |
reps |
number of random simulation repetitions |
spatial_network_name |
which spatial network to use for binSpectSingle |
spat_methods |
vector of spatial methods to test |
spat_methods_params |
list of parameters list for each element in the vector of spatial methods to test |
spat_methods_names |
name for each element in the vector of spatial elements to test |
save_plot |
save intermediate random simulation plots or not |
save_dir |
directory to save results to |
max_col |
maximum number of columns for final plots |
height |
height of final plots |
width |
width of final plots |
run_simulations |
run simulations (default = TRUE) |
... |
additional parameters for spatial gene detection tests |
data.table with results
1 | runPatternSimulation(gobject)
|
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