R/datasets.R

In biosigner: Signature discovery from omics data

#' Analysis of plasma from diabetic patients by LC-HRMS
#'
#' Plasma samples from 69 diabetic patients were analyzed by reversed-phase
#' liquid chromatography coupled to high-resolution mass spectrometry (Orbitrap
#' Exactive) in the negative ionization mode. The raw data were pre-processed
#' with XCMS and CAMERA (5,501 features), corrected for signal drift, log10
#' transformed, and annotated with an in-house spectral database. The patient's
#' age, body mass index, and diabetic type are recorded. These three clinical
#' covariates are strongly associated, most of the type II patients being older
#' and with a higher bmi than the type I individuals.
#'
#' @name diaplasma
#' @docType data
#' @format A list with the following elements:
#' \itemize{
#' \item dataMatrix: a 69 samples x
#' 5,501 features matrix of numeric type corresponding to the intensity
#' profiles (values have been log10-transformed),
#' \item sampleMetadata: a 69 x 3 data frame, with the patients' diabetic type
#' ('type', factor), age ('age', numeric), and body mass index ('bmi', numeric),
#' \item variableMetadata: a 5,501 x 8 data frame, with the median m/z ('mzmed',
#' numeric) and the median retention time in seconds ('rtmed', numeric) from
#' XCMS, the 'isotopes' (character), 'adduct' (character) and 'pcgroups'
#' (numeric) annotations from CAMERA, and the names of the m/z and RT matching
#' compounds from an in-house database of pure spectra from commercial
#' metabolites ('spiDb', character).
#' }
#' @return List containing the 'dataMatrix' matrix (numeric) of data (samples
#' as rows, variables as columns), the 'sampleMetadata' data frame of sample
#' metadata, and the variableMetadata data frame of variable metadata. Row
#' names of 'dataMatrix' and 'sampleMetadata' are identical. Column names of
#' 'dataMatrix' are identical to row names of 'variableMetadata'. For details
#' see the 'Format' section above.
#' @references Rinaudo P., Boudah S., Junot C. and Thevenot E.A. (2016).
#' biosigner: a new method for the discovery of significant molecular signatures
#' from omics data. Frontiers in Molecular Biosciences 3.
#' doi:10.3389/fmolb.2016.00026
#' @source 'diaplasma' dataset.
#' @keywords datasets
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