% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{example_multiomics}
\alias{example_multiomics}
\title{Example Multi-Omics Dataset for MultiOmicsBridge}
\format{
A named list with 6 elements. See Details.
}
\source{
Generated by \code{inst/scripts/make_example_data.R}. All data are
simulated; no real patient data is included.
}
\value{
A named list with 6 elements: \code{host_se}, \code{mb_se},
  \code{mae}, \code{outcome}, \code{metadata}, and \code{ground_truth}.
  See Details for full descriptions of each element.
}
\description{
A small, self-contained simulated paired multi-omics dataset inspired by
inflammatory bowel disease (IBD) biology. This dataset is used throughout
package examples, tests, and the vignette to demonstrate the complete
MultiOmicsBridge analysis pipeline.
}
\details{
The dataset is a named list stored as an RDS file in
\code{inst/extdata/example_multiomics.rds}. It contains 30 samples
(15 ulcerative colitis [UC], 15 healthy controls) with paired host
transcriptomics (800 genes) and gut microbiome (60 taxa) measurements.

\strong{Data provenance:} All data are computationally simulated (not
derived from real patient data). Host RNA-seq counts are drawn from a
negative binomial distribution (\code{rnbinom(mu=180, size=3)}) with
IBD-associated fold changes injected for 25 signal genes.
Microbiome counts are drawn from \code{rnbinom(mu=600, size=2)} with
dysbiosis fold changes for 15 signal taxa. A deliberate cross-omics
correlation between CXCL8 (host) and Ruminococcus_gnavus (microbiome)
is injected to test biomarker network recovery.
The random seed is \code{set.seed(2026L)}.

\strong{List elements:}
\describe{
  \item{\code{host_se}}{A
    \code{\link[SummarizedExperiment]{SummarizedExperiment}}
    with 800 genes (rows) x 30 samples (columns). Contains raw counts
    and voom-normalized assays. Includes 15 IBD-upregulated genes
    (CXCL8, S100A8, IL6, TNF, etc.), 10 IBD-downregulated genes
    (MUC2, TFF3, etc.), and 775 neutral background genes.}
  \item{\code{mb_se}}{A
    \code{\link[SummarizedExperiment]{SummarizedExperiment}}
    with 60 taxa (rows) x 30 samples (columns). Contains raw counts
    and CLR-normalized assays. Includes 8 UC-enriched taxa
    (Ruminococcus_gnavus, Escherichia_coli, etc.), 7 UC-depleted taxa
    (Faecalibacterium_prausnitzii, Roseburia_intestinalis, etc.),
    and 45 neutral background taxa.}
  \item{\code{mae}}{A
    \code{\link[MultiAssayExperiment]{MultiAssayExperiment}}
    combining both omics layers with matched sample mappings.}
  \item{\code{outcome}}{A character vector of length 30 with values
    \code{"UC"} (first 15) and \code{"Control"} (last 15).}
  \item{\code{metadata}}{A \code{data.frame} with 30 rows and columns:
    \code{condition}, \code{age}, \code{sex}, \code{bmi},
    \code{disease_duration_yrs} (NA for controls).}
  \item{\code{ground_truth}}{A list containing known signal features
    for validation: \code{ibd_up_genes} (15 gene names),
    \code{ibd_down_genes} (10 gene names), \code{uc_up_taxa}
    (8 taxon names), \code{uc_down_taxa} (7 taxon names), and
    \code{correlated_pair} (CXCL8 and Ruminococcus_gnavus).}
}
}
\examples{
ex <- readRDS(system.file("extdata", "example_multiomics.rds",
                           package = "MultiOmicsBridge"))
names(ex)
ex$mae
table(ex$outcome)
head(ex$metadata)

}
\seealso{
\code{\link{MultiOmicsBridgeAnalysis}},
  \code{\link{loadHostData}}, \code{\link{loadMicrobiomeData}},
  \code{\link{matchSamples}}
}
\keyword{datasets}
