% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{valencia2k}
\alias{valencia2k}
\title{Valencia 2k vaginal microbiome dataset}
\format{
A list with five components:
\describe{
\item{rel}{Numeric matrix (2000 x 178). Compositional relative abundances;
each row sums to 1. Rows are samples, columns are taxonomic features.}
\item{cst}{Data frame (2000 x 3) with columns:
\code{sample_id} (character),
\code{Val_CST} (Valencia CST assignment: I, II, III, IV-A, IV-B, IV-C, V),
\code{Val_subCST} (Valencia sub-CST assignment: I-A, I-B, II, III-A, III-B,
IV-A, IV-B, IV-C0, IV-C1, IV-C2, IV-C3, IV-C4, V).}
\item{reads}{Integer vector of length 2000. Per-sample read counts after
taxonomic filtering. Use \code{sweep(valencia2k$rel, 1, valencia2k$reads, "*")}
to reconstruct a count-like matrix.}
\item{taxa}{Character vector of 178 taxon names (column names of \code{rel}).}
\item{source}{Character string documenting provenance.}
}
}
\source{
Subsampled from the VALENCIA training data at
\url{https://github.com/ravel-lab/VALENCIA}. See
\code{data-raw/build_valencia2k.R} and the installed
\code{DATA_PROVENANCE.md} file for construction and licensing details.
}
\usage{
valencia2k
}
\description{
A stratified subsample of 2,000 vaginal samples from the Valencia 13k
CST-classifier training set (France et al. 2020), bundled as an example
dataset for demonstrating dCST construction after L-infinity normalization.
}
\details{
The subsample preserves proportional representation of all 13 Valencia
sub-CSTs and was drawn with \code{set.seed(42)}.

The Valencia CST classifier (France et al. 2020) assigns vaginal microbiome
samples to community state types (CSTs) based on nearest-centroid
classification in relative-abundance space. The original training set
contains 12,881 samples and 178 taxonomic features after filtering.

This 2,000-sample subsample is intended for vignette demonstrations. The
compositional matrix can be used directly with \code{\link{normalize.linf}}
and downstream dCST functions. For workflows that require count-like input,
reconstruct approximate counts using the \code{reads} vector.
}
\examples{
data(valencia2k)
dim(valencia2k$rel)           # 2000 x 178
table(valencia2k$cst$Val_CST) # CST distribution
head(valencia2k$taxa, 10)     # first 10 taxon names

}
\references{
France, M. T., Ma, B., Gajer, P., Brown, S., Humphrys, M. S., Holm, J. B.,
Waetjen, L. E., Brotman, R. M., & Ravel, J. (2020). VALENCIA: a nearest
centroid classification method for vaginal microbial communities based on
composition. \emph{Microbiome}, 8(1), 166.
\doi{10.1186/s40168-020-00934-6}
}
\keyword{datasets}
