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##class descriptions go in here
################################## Classes ################################
#' @title 'metabData' Single Metabolomics Dataset Class
#'
#' @description
#' This class is designed to process and format input metabolomics feature
#' tables. It stores the information from individual metabolomics datasets,
#' including the formatted feature table, sample names, and feature statistics.
#'
#' @slot data formatted metabolomics data frame.
#'
#' @slot samples character vector of analyzed sample names
#'
#' @slot extra character vector of non-analyzed columns names
#'
#' @slot stats A list of dataset statistics
#'
#' @export
setClass("metabData", slots = c(data = "data.frame",
samples = "character",
extra = "character",
stats = "list"),
prototype = prototype(
data = data.frame(),
samples = character(),
extra = character(),
stats = list()
)
)
#' @title 'metabCombiner' Combined Metabolomics Dataset Class
#'
#' @description
#' This is the main object for the \code{metabCombiner} package workflow. This
#' object holds a combined feature table, along with a retention time
#' projection model, the ordered pair anchors used to generate this model, and
#' key object statistics.
#'
#' @slot combinedTable data.frame displaying all feature pair alignments,
#' combining measurements of all possible shared compounds
#'
#' @slot nonmatched list of data frames consisting of nonmatched features
#'
#' @slot anchors data.frame of of feature alignments used for rt modeling
#'
#' @slot model list containing the last fitted nonlinear model(s)
#'
#' @slot coefficients list of last used A,B,C similarity weight values
#'
#' @slot samples list of sample name vectors from input datasets
#'
#' @slot extra list of extra column name vectors from input datasets
#'
#' @slot stats set of useful metabCombiner statistics
#'
#' @export
setClass("metabCombiner", slots = c(combinedTable = "data.frame",
nonmatched = "list",
anchors = "data.frame",
model = "list",
coefficients = "list",
samples = "list",
extra = "list",
stats = "list"
),
prototype = prototype(
combinedTable = data.frame(),
nonmatched = list(),
anchors = data.frame(),
model = list(),
coefficients = list(),
samples = list(),
extra = list(),
stats = list()
)
)
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