% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data-AD_data.r
\docType{data}
\name{AD_data}
\alias{AD_data}
\title{Anaerobic digestion study}
\format{
A list containing three TreeSummarizedExperiment objects
\code{FullData}, \code{EgData} and \code{CorrectData}:
\describe{
\item{FullData}{A TreeSummarizedExperiment object containing the counts of 75
samples and 567 OTUs. The meta data information of each sample is stored in
the rowData, while the taxonomy of each OTU is stored in the colData.}
\item{EgData}{A TreeSummarizedExperiment object containing the values of 75
samples and 231 OTUs filtered and centered log ratio transformed from the
\code{FullData} with raw counts.The rowData includes \code{Y.trt} and
\code{Y.bat}. \code{Y.trt} is the effect of interest, which is a factor of
phenol concentrations for each sample in the AD study; \code{Y.bat} is the
batch effect, which is a factor of sample processing dates for each sample.
The taxonomy of each OTU is stored in the colData. The rowTree is built based
on the \code{Y.bat}.}
\item{CorrectData}{A TreeSummarizedExperiment object containing seven
datasets before or after batch effect correction using different methods.
Each assay includes 75 samples and 231 OTUs.}}
}
\source{
The raw data were provided by Dr. Olivier Chapleur and published at
the referenced article. Filtering and normalisation described in our package
vignette.
}
\usage{
data('AD_data')
}
\value{
None.
}
\description{
This study explored the microbial indicators that could improve the efficacy
of anaerobic digestion (AD) bioprocess and prevent its failure. The samples
were treated with two different ranges of phenol concentration (effect of
interest) and processed at five different dates (batch effect). This study
includes a clear and strong batch effect with an approx. balanced
batch x treatment design.
}
\references{
\insertRef{chapleur2016increasing}{PLSDAbatch}
}
\keyword{datasets}