% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotClassifierComparison.R
\name{plotClassifierComparison}
\alias{plotClassifierComparison}
\title{ROC Curve Comparison of Host-Only, Microbiome-Only, and Joint Classifiers}
\usage{
plotClassifierComparison(
  result,
  type = c("roc", "bar"),
  colours = c(host_only = "#4CAF50", microbiome_only = "#FF9800", joint = "#2196F3"),
  show_diagonal = TRUE,
  linewidth = 0.9
)
}
\arguments{
\item{result}{A \code{\link{MOBResult}} object from
\code{\link{MultiOmicsBridgeAnalysis}}.}

\item{type}{A \code{character(1)}, either \code{"roc"} (ROC curves
from the last CV fold) or \code{"bar"} (bar chart of mean CV AUC
values). Default: \code{"roc"}.}

\item{colours}{A named \code{character} vector of colours for
\code{"host_only"}, \code{"microbiome_only"}, and \code{"joint"}.
Default: a colour-blind-friendly palette.}

\item{show_diagonal}{Logical. If \code{TRUE}, overlay the chance-level
diagonal (AUC = 0.5 reference line). Default: \code{TRUE}.}

\item{linewidth}{A \code{numeric(1)} line width for ROC curves.
Default: \code{0.9}.}
}
\value{
A \code{ggplot2} object.
}
\description{
Produces overlaid ROC (Receiver Operating Characteristic) curves
comparing the three diagnostic classifier configurations — host
transcriptomics only, gut microbiome only, and the joint multi-omics
model — on the same axes. The AUC-ROC values are annotated on the
plot, making the multi-omics advantage immediately visible. A
bar chart of mean cross-validated AUC values is also available via
\code{type = "bar"}.
}
\examples{
set.seed(42)
host_counts <- matrix(rpois(500 * 20, 100), nrow = 500, ncol = 20,
    dimnames = list(paste0("Gene", 1:500), paste0("S", 1:20)))
host_counts[1:20, 11:20] <- host_counts[1:20, 11:20] * 5L
mb_counts <- matrix(rpois(60 * 20, 40), nrow = 60, ncol = 20,
    dimnames = list(paste0("Taxon", 1:60), paste0("S", 1:20)))

host_se <- loadHostData(host_counts)
mb_se   <- loadMicrobiomeData(mb_counts)
mae     <- matchSamples(host_se, mb_se)
outcome <- rep(c("ctrl", "treat"), each = 10)
result  <- MultiOmicsBridgeAnalysis(mae, outcome,
                                     n_components = 2,
                                     n_features_host = 20,
                                     n_features_mb = 10,
                                     n_biomarkers = 15, cv_folds = 3)
plotClassifierComparison(result, type = "bar")

}
\seealso{
\code{\link{MultiOmicsBridgeAnalysis}},
  \code{\link{diagnosticClassifier}}, \code{\link{performance}}
}
