ROC Curves by Comparison (ggplot2) — benchmark_roc

Generates ROC curves for each comparison using pROC::ggroc(). Requires the pROC package.

Usage

benchmark_roc_gg(
  classified_df,
  p_col = "adj.P.Val",
  comparisons = NULL,
  title = "ROC Curves by Comparison",
  zoom = FALSE,
  palette = "Set1"
)

Arguments

classified_df: Classified data frame (output of .classify_all_comparisons)
p_col: P-value column name used as predictor score
comparisons: Comparisons to include (NULL = all)
title: Plot title
zoom: If TRUE, zoom into the low-FPR region (x = 0 to 0.1)
palette: RColorBrewer palette name (default: "Set1")

Value

ggplot2 object or NULL if pROC is not available

Examples

data(nadia_dia)
de <- process_proteomics(nadia_dia, verbose = FALSE)$DEPs_results
sp <- utils::read.delim(system.file("extdata", "nadia_dia_spikein.tsv.gz",
                                    package = "NADIA"))
de$Species <- sp$PG.OrganismId[match(de$Protein.IDs, sp$PG.ProteinGroups)]
ev <- data.frame(Comparison = rep(c("B-A", "D-A"), each = 2),
                 Species = c("ECOLI", "YEAST"),
                 expected_logFC = c(1, -0.58, 2, -3.3))
if (requireNamespace("pROC", quietly = TRUE)) {
  bench <- benchmarking_proteomics(de, ev, verbose = FALSE)
  benchmark_roc_gg(bench$classified_df, comparisons = "B-A")
}