Add simulations to explore the impact of mean parameters

code/simulate-data.R

@@ -46,6 +46,14 @@ params <- setParam(params, "batchCells", sim_pars$batchCells)
 params <- setParam(params, "seed", sim_pars$seed)
 params <- setParam(params, "de.facLoc", sim_pars$de.facLoc)
 
+if (!is.null(sim_pars$mean.shape)) {
+  params <- setParam(params, "mean.shape", sim_pars$mean.shape)
+}
+
+if (!is.null(sim_pars$mean.rate)) {
+  params <- setParam(params, "mean.rate", sim_pars$mean.shape)
+}
+
 Sys.time()
 
 # Run the splatter simulation.

code/simulation-pars.R

@@ -128,13 +128,30 @@ de_facloc_sims <- expand_grid(
     file_name = paste0(label, "_", rep)
   )
 
+mean_sims <- expand_grid(
+  label = "standard_sim",
+  data_id = "pbmc3k",
+  mean.shape = 1,
+  mean.rate = c(4, 3, 2),
+  rep = 1:2,
+  batchCells = 2000,
+  n_clus = 5,
+  group.prob = list(rep(1 / 5, 5)),
+) %>%
+  rowid_to_column %>%
+  mutate(
+    seed = 7000 + rowid,
+    file_name = paste0(label, "_", rep)
+  )
+
 all_sim_pars <- list(
   standard_sims,
   null_sims,
   num_cells_sims,
   num_clusters_sims,
   proportion_sims,
-  de_facloc_sims
+  de_facloc_sims,
+  mean_sims
 )
 
 sim_pars <- flatten(map(all_sim_pars, ~ transpose(.x, .names = .x$file_name)))