- Added tests to ensure sccomp_boxplot can accept additional ggplot layers, improving flexibility for users.

- Updated vignettes to reflect changes in function usage and added examples for custom ggplot layers.

Author: stemangiola

NAMESPACE

@@ -154,4 +154,3 @@ importFrom(tidyr,unnest)
 importFrom(tidyselect,all_of)
 importFrom(tidyselect,last_col)
 importFrom(utils,data)
-importFrom(utils,packageVersion)

R/sccomp_boxplot.R

@@ -71,15 +71,23 @@ sccomp_boxplot = function(
     .data |>
 
     # Otherwise does not work
-    select(-`factor`) |>
+    filter(factor == !!factor) |> 
+    select(-`factor`)
+  
+  data_proportion = 
+    
+    data_proportion |>
 
     pivot_wider(names_from = parameter, values_from = c(contains("c_"), contains("v_"))) |>
     left_join(
       attr(.data, "count_data") ,
       by = quo_name(.cell_group)
     ) |>
     with_groups(!!.sample, ~ mutate(.x, proportion = (!!.count)/sum(!!.count)) ) |> 
-    mutate(is_zero = proportion==0) 
+    mutate(is_zero = proportion==0) |> 
+    
+    # Add columns for plotting expansion
+    left_join(data_proportion |> select(cell_group, parameter, c_pH0, c_FDR, v_pH0, v_FDR))
 
   if(remove_unwanted_effects){
     .data_adjusted = 
@@ -236,7 +244,7 @@ plot_boxplot = function(
         with_groups(c(!!.cell_group, !!as.symbol(factor_of_interest)), ~ .x %>% summarise(name = paste(name, collapse = ", ")))
   }
 
-  my_boxplot = ggplot()
+  my_boxplot = data_proportion |> ggplot()
 
   if("fit" %in% names(attributes(.data))){
 

R/simulate_data.R

@@ -45,32 +45,33 @@
 #' S. Mangiola, A.J. Roth-Schulze, M. Trussart, E. Zozaya-Valdés, M. Ma, Z. Gao, A.F. Rubin, T.P. Speed, H. Shim, & A.T. Papenfuss, sccomp: Robust differential composition and variability analysis for single-cell data, Proc. Natl. Acad. Sci. U.S.A. 120 (33) e2203828120, https://doi.org/10.1073/pnas.2203828120 (2023).
 #'
 #' @export
+#' @noRd
+#' @keywords internal
 #'
 #' @examples
 #'
-#' print("cmdstanr is needed to run this example.")
+#' # print("cmdstanr is needed to run this example.")
 #' # Note: Before running the example, ensure that the 'cmdstanr' package is installed:
 #' # install.packages("cmdstanr", repos = c("https://stan-dev.r-universe.dev/", getOption("repos")))
 #'
-#' \donttest{
-#'   if (instantiate::stan_cmdstan_exists()) {
-#'     data("counts_obj")
-#'     library(dplyr)
+#' # \donttest{
+#' #   if (instantiate::stan_cmdstan_exists()) {
+#' #     data("counts_obj")
+#' #     library(dplyr)
 #'
-#'     estimate = sccomp_estimate(
-#'       counts_obj,
-#'       ~ type, ~1, "sample", "cell_group", "count",
-#'       cores = 1
-#'     )
+#' #     estimate = sccomp_estimate(
+#' #       counts_obj,
+#' #       ~ type, ~1, "sample", "cell_group", "count",
+#' #       cores = 1
+#' #     )
 #'
-#'     # Set coefficients for cell_groups. In this case all coefficients are 0 for simplicity.
-#'     counts_obj = counts_obj |> mutate(b_0 = 0, b_1 = 0)
-#'
-#'     # Simulate data
-#'     simulate_data(counts_obj, estimate, ~type, ~1, sample, cell_group, c(b_0, b_1))
-#'   }
-#' }
+#' #     # Set coefficients for cell_groups. In this case all coefficients are 0 for simplicity.
+#' #     counts_obj = counts_obj |> mutate(b_0 = 0, b_1 = 0)
 #'
+#' #     # Simulate data
+#' #     simulate_data(counts_obj, estimate, ~type, ~1, sample, cell_group, c(b_0, b_1))
+#' #   }
+#' # }
 simulate_data <- function(.data,
                           .estimate_object,
                           formula_composition,

man/simulate_data.Rd

@@ -1,6 +1,7 @@
 library(dplyr)
 library(tidyr)
 library(sccomp)
+library(ggplot2)
 data("seurat_obj")
 data("sce_obj")
 data("counts_obj")
@@ -325,4 +326,32 @@ test_that("plot_2D_intervals includes regression line from prec_coeff parameters
         show_fdr_message = FALSE
       )
   )
+}) 
+
+test_that("sccomp_boxplot can accept additional ggplot layers", {
+   skip_cmdstan()
+  
+  # Test that we can add layers to the boxplot
+  plot_with_label <- my_estimate |> 
+    sccomp_test() |> 
+    sccomp_boxplot("type", significance_threshold = 0.025) +
+    geom_label(aes(label = c_FDR), x = 1, y = 0.5)
+  
+  expect_s3_class(plot_with_label, "ggplot")
+  
+  # Test with geom_text
+  plot_with_text <- my_estimate |> 
+    sccomp_test() |> 
+    sccomp_boxplot("type", significance_threshold = 0.025) +
+    geom_text(aes(label = c_FDR), x = 1, y = 0.3)
+  
+  expect_s3_class(plot_with_text, "ggplot")
+  
+  # Test with theme modifications
+  plot_with_theme <- my_estimate |> 
+    sccomp_test() |> 
+    sccomp_boxplot("type", significance_threshold = 0.025) +
+    theme(plot.title = element_text(color = "red"))
+  
+  expect_s3_class(plot_with_theme, "ggplot")
 })