R/vaginal_meta-data.R

In MMUPHin: Meta-analysis Methods with Uniform Pipeline for Heterogeneity in Microbiome Studies

#' Sample metadata of two public vaginal studies
#'
#' Metadata information of vaginal samples in the two public studies provided in
#' \code{\link[curatedMetagenomicData]{curatedMetagenomicData}}.
#'
#' @docType data
#'
#' @usage data(vaginal_meta)
#'
#' @format A \code{data.frame} of per-sample metadata information
#'
#' @references Pasolli, Edoardo, Lucas Schiffer, Paolo Manghi, Audrey Renson, 
#' Valerie Obenchain, Duy Tin Truong, Francesco Beghini et al. "Accessible, 
#' curated metagenomic data through ExperimentHub." Nature methods 14, no. 11 
#' (2017): 1023.
#'
#' @source \code{\link[curatedMetagenomicData]{curatedMetagenomicData}}
#'
#' @examples
#' data(vaginal_meta)
#' # has vaginal samples across two studies
#' table(vaginal_meta$studyID, vaginal_meta$body_site)
#' # The following were used to generate the object
#' # library(curatedMetagenomicData)
#' # library(phyloseq)
#' # datasets <- curatedMetagenomicData(
#' #   "*metaphlan_bugs_list.vagina*",
#' #   dryrun = FALSE)
#' # Construct phyloseq object from the five datasets
#' # physeq <-
#'   # Aggregate the five studies into ExpressionSet
#' #   mergeData(datasets) %>%
#'   # Convert to phyloseq object
#' #   ExpressionSet2phyloseq() %>%
#'   # Subset features to species
#' #   subset_taxa(!is.na(Species) & is.na(Strain)) %>%
#'   # Normalize abundances to relative abundance scale
#' #   transform_sample_counts(function(x) x / sum(x)) %>%
#'   # Filter features to be of at least 1e-5 relative abundance in two samples
#' #   filter_taxa(kOverA(2, 1e-5), prune = TRUE)
#' # vaginal_meta <- data.frame(sample_data(physeq))
#' # vaginal_meta$studyID <- factor(vaginal_meta$studyID)
"vaginal_meta"