re-render

analyses/cell-type-consensus/exploratory-notebooks/03-osteosarcoma-consensus-celltypes.Rmd

@@ -194,7 +194,7 @@ We have already looked at this in `02-explore-consensus-results.Rmd`, but here w
 all_results_df <- all_results_df |> 
   dplyr::mutate(
     # get most frequently observed cell types across libraries in that project 
-    top_celltypes = forcats::fct_lump_n(consensus_annotation, 10, other_level = "All remaining cell types", ties.method = "first") |> 
+    top_celltypes = forcats::fct_lump_n(consensus_annotation, 15, other_level = "All remaining cell types", ties.method = "first") |> 
       # sort by frequency 
       forcats::fct_infreq() |> 
       # make sure all remaining and unknown are last, use this to assign colors in specific order
@@ -236,6 +236,13 @@ Generally, we see most annotated cells are smooth muscle cells and endothelial c
 There also appears to be some samples that have macrophages and/or T cell populations. 
 We also see a handful of samples that don't have any cells that are annotated.
 
+```{r}
+stacked_barchart(total_order_df, fill_color = "top_celltypes", facet_variable = "project_id", colors = all_celltype_colors)
+```
+
+It looks like both total number of cells that are classified and composition of those cells is project dependent. 
+This makes sense since sample prep is probably different across labs. 
+
 ## Immune cell populations
 
 Let's look specifically at immune cell populations.