% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{agp_gut}
\alias{agp_gut}
\title{American Gut Project gut microbiome dataset}
\format{
A list with four components:
\describe{
\item{counts}{Integer matrix (766 x 314). Raw 16S V4 read counts.
Rows are samples, columns are SILVA species-level taxa.}
\item{meta}{Data frame (766 rows) with columns:
\code{Run} (SRA run accession),
\code{dcst_depth1}, \code{dcst_depth2} (pre-computed dCST labels),
\code{IBS}, \code{IBD}, \code{Diabetes}, \code{Autoimmune},
\code{Seasonal_allergies}, \code{Migraine}, \code{Acid_reflux},
\code{Lung_disease}, \code{Cardiovascular_disease}, \code{Skin_condition},
\code{Obesity} (binary disease indicators from self-reported AGP metadata),
\code{BMI} (numeric, self-reported), and
\code{selection_reason} (target-dCST inclusion or seeded background
sampling).}
\item{taxa}{Character vector of 314 SILVA taxonomy strings.}
\item{source}{Character string documenting provenance.}
}
}
\source{
Derived from the public American Gut Project records under ENA accession
\href{https://www.ebi.ac.uk/ena/browser/view/PRJEB11419}{PRJEB11419} via the
PRIME pipeline. See \code{data-raw/create_agp_gut_subset.py},
\code{data-raw/build_agp_gut.R}, and the installed
\code{DATA_PROVENANCE.md} file.
}
\usage{
agp_gut
}
\description{
A stratified subsample of 766 gut microbiome samples from the American Gut
Project (PRJEB11419, AGP-US-2015), bundled for demonstrating L-infinity
dCST construction in a gut ecosystem.
}
\details{
The subsample includes all samples assigned to four uncommon demonstration
dCSTs (Prevotella_7, Pasteurellaceae, Akkermansia, and Staphylococcus).
The remaining slots are a simple random sample, drawn with seed 42, from
the eligible background after excluding Eukaryota and Unassigned labels.
Phenotype fields are joined only after membership is fixed and do not
influence selection. Because inclusion probabilities differ by dCST, this
object is a computational demonstration dataset rather than a probability
sample of the underlying cohort.

The American Gut Project is a large citizen-science 16S rRNA survey of the
human microbiome. Health conditions are self-reported via questionnaire and
should be interpreted with appropriate caution.

The phenotype fields must not be used with this dCST-stratified subset for
population prevalence estimates, effect-size estimation, or association
testing. The exact selection is generated by
\code{data-raw/create_agp_gut_subset.py}; run-ID membership, selection
reasons, and derived annotations are retained in
\code{inst/extdata/agp_gut_meta.csv}.

The count matrix can be used directly with \code{\link{filter.asv}},
\code{\link{normalize.linf}}, and downstream dCST functions.

Note on Escherichia-Shigella: this genus is inflated in 16S V4 data due to
primer cross-reactivity and should be interpreted with caution.
}
\examples{
data(agp_gut)
dim(agp_gut$counts)                     # 766 x 314
table(agp_gut$meta$dcst_depth1)         # dCST distribution
sum(agp_gut$meta$IBS)                   # IBS cases

}
\references{
McDonald, D., Hyde, E., Debelius, J. W., et al. (2018). American Gut: an
Open Platform for Citizen Science Microbiome Research. \emph{mSystems},
3(3), e00031-18. \doi{10.1128/mSystems.00031-18}
}
\keyword{datasets}
