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ECDF of Per-peptide Prevalences for Two Groups

Source: R/delta_plots.R
ecdf_plot.Rd

Plot empirical cumulative distribution functions (ECDFs) of per-peptide prevalence for two groups using a ph_compute_prevalence()-style table. The plot compares the cumulative distribution of prevalence values between the two groups and optionally annotates median shifts and a Kolmogorov-Smirnov (KS) test summary.

Usage

ecdf_plot(
  prev_tbl,
  group_pair_values = NULL,
  group_labels = NULL,
  line_width_pt = 1,
  line_alpha = 1,
  group1_line_color = "#1f77b4",
  group2_line_color = "#d62728",
  show_median_lines = TRUE,
  show_ks_test = TRUE,
  plot_title = NULL,
  plot_subtitle = NULL,
  x_label = NULL,
  y_label = NULL
)

Arguments

prev_tbl

Data frame with columns group1, group2, prop1, prop2. Optional feature columns are ignored.

group_pair_values

Optional length-2 character vector c(group1, group2). Use this when prev_tbl contains multiple group pairs.

group_labels

Optional length-2 character vector of display labels c(label_group1, label_group2). Defaults to group1/group2.

line_width_pt

Line width for ECDF steps (ggplot units). Default 1.0.

line_alpha

Line alpha for ECDF steps. Default 1.0.

group1_line_color, group2_line_color

Line colors for group1 and group2.

show_median_lines

Logical; add median lines. Default TRUE.

show_ks_test

Logical; add KS test summary to subtitle. Default TRUE.

plot_title, plot_subtitle

Optional plot labels.

x_label, y_label

Optional axis labels.

Value

A ggplot object.

Details

Each group is represented by a step function showing the fraction of features with prevalence less than or equal to a given value. Vertical median lines can be added for each group, and the subtitle can include the KS statistic and p-value along with the median difference.

Examples

set.seed(4)
n <- 50
prev_tbl <- data.frame(
  feature = paste0("pep", seq_len(n)),
  group1  = "A",
  group2  = "B",
  prop1   = runif(n),
  prop2   = runif(n)
)

p <- ecdf_plot(
  prev_tbl,
  group_pair_values = c("A", "B"),
  group_labels      = c("Group A", "Group B"),
  show_ks_test      = TRUE
)
print(p)