SDjoygret: Testing R Package

#' Sacurine data from ropls
#'
#' Urine samples from 183 human adults were analyzed by liquid chromatography coupled to high-resolution
#' mass spectrometry (LTQ Orbitrap) in the negative ionization mode. A total of 109 metabolites were
#' identified or annotated at the MSI level 1 or 2. After retention time alignment with XCMS, peaks were
#' integrated with Quan Browser. After signal drift and batch effect correction of intensities, each urine
#' profile was normalized to the osmolality of the sample. Finally, the data were log10 transformed.
#'
#' @docType data
#' @usage data(sacurine.dlist)
#' @format A dlist : three levels list of tbl (Datamatrix, SampleMetadata, VariableMetadata)
#' @keywords datasets
#' @references Thevenot E.A., Roux A., Xu Y., Ezan E. and Junot C. (2015). Analysis of the human adult urinary
#' metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for
#'  univariate and OPLS statistical analyses. Journal of Proteome Research, DOI: 10.1021/acs.jproteome.5b00354
#' @source From ropls package, data : sacurine
#' @examples
#' data(sacurine.dlist)
"sacurine.dlist"

#' Sacurine data from ropls
#'
#' Urine samples from 183 human adults were analyzed by liquid chromatography coupled to high-resolution
#' mass spectrometry (LTQ Orbitrap) in the negative ionization mode. A total of 109 metabolites were
#' identified or annotated at the MSI level 1 or 2. After retention time alignment with XCMS, peaks were
#' integrated with Quan Browser. After signal drift and batch effect correction of intensities, each urine
#' profile was normalized to the osmolality of the sample. Finally, the data were log10 transformed.
#'
#' @docType data
#' @usage data(sacurine.dlist)
#' @format A dlist : three levels list of data.frame (Datamatrix, SampleMetadata, VariableMetadata)
#' @keywords datasets
#' @references Thevenot E.A., Roux A., Xu Y., Ezan E. and Junot C. (2015). Analysis of the human adult urinary
#' metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for
#'  univariate and OPLS statistical analyses. Journal of Proteome Research, DOI: 10.1021/acs.jproteome.5b00354
#' @source From ropls package, data : sacurine
#' @examples
#' data(sacurine.dlist)
"sacurine.df"

#' Sacurine data from ropls
#'
#' Urine samples from 183 human adults were analyzed by liquid chromatography coupled to high-resolution
#' mass spectrometry (LTQ Orbitrap) in the negative ionization mode. A total of 109 metabolites were
#' identified or annotated at the MSI level 1 or 2. After retention time alignment with XCMS, peaks were
#' integrated with Quan Browser. After signal drift and batch effect correction of intensities, each urine
#' profile was normalized to the osmolality of the sample. Finally, the data were log10 transformed.
#'
#' @docType data
#' @usage data(sacurine.dlist)
#' @format A dlist : three levels list of data.table (Datamatrix, SampleMetadata, VariableMetadata)
#' @keywords datasets
#' @references Thevenot E.A., Roux A., Xu Y., Ezan E. and Junot C. (2015). Analysis of the human adult urinary
#' metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for
#'  univariate and OPLS statistical analyses. Journal of Proteome Research, DOI: 10.1021/acs.jproteome.5b00354
#' @source From ropls package, data : sacurine
#' @examples
#' data(sacurine.dlist)
"sacurine.dt"

#' Sacurine data from ropls
#'
#' Urine samples from 183 human adults were analyzed by liquid chromatography coupled to high-resolution
#' mass spectrometry (LTQ Orbitrap) in the negative ionization mode. A total of 109 metabolites were
#' identified or annotated at the MSI level 1 or 2. After retention time alignment with XCMS, peaks were
#' integrated with Quan Browser. After signal drift and batch effect correction of intensities, each urine
#' profile was normalized to the osmolality of the sample. Finally, the data were log10 transformed.
#'
#' @docType data
#' @usage data(sacurine.dlist)
#' @format A dlist : three levels list of tibbles (Datamatrix, SampleMetadata, VariableMetadata)
#' @keywords datasets
#' @references Thevenot E.A., Roux A., Xu Y., Ezan E. and Junot C. (2015). Analysis of the human adult urinary
#' metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for
#'  univariate and OPLS statistical analyses. Journal of Proteome Research, DOI: 10.1021/acs.jproteome.5b00354
#' @source From ropls package, data : sacurine
#' @examples
#' data(sacurine.dlist)
"sacurine.tbl"