sccomp_boxplot

This function plots a boxplot of the results of the model.

sccomp_boxplot(
  .data,
  factor,
  significance_threshold = 0.05,
  test_composition_above_logit_fold_change = attr(.data,
    "test_composition_above_logit_fold_change")
)

Arguments

.data

A tibble including a cell_group name column | sample name column | read counts column | factor columns | Pvalue column | a significance column

factor

A character string for a factor of interest included in the model

significance_threshold

A real. FDR threshold for labelling significant cell-groups.

test_composition_above_logit_fold_change

A positive integer. It is the effect threshold used for the hypothesis test. A value of 0.2 correspond to a change in cell proportion of 10% for a cell type with baseline proportion of 50%. That is, a cell type goes from 45% to 50%. When the baseline proportion is closer to 0 or 1 this effect thrshold has consistent value in the logit uncontrained scale.

Value

A ggplot

Examples

message("Use the following example after having installed install.packages(\"cmdstanr\", repos = c(\"https://stan-dev.r-universe.dev/\", getOption(\"repos\")))")
#> Use the following example after having installed install.packages("cmdstanr", repos = c("https://stan-dev.r-universe.dev/", getOption("repos")))

# \donttest{
  if (instantiate::stan_cmdstan_exists()) {
    data("counts_obj")

    estimate = sccomp_estimate(
      counts_obj,
      ~ type, ~1, sample, cell_group, count,
      cores = 1
    ) |>
    sccomp_test()

    # estimate |> sccomp_boxplot()
  }
# }