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documenting prepareData + a typo
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R/prepareData.R

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#' Prepare proteomics data for analysis
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#' Prepare proteomics data for analysis.
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#'
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#' @param data_path A character containing the path to an .xlsx file.
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#' @param intensity_columns An integer vector containing the intensity columns of the table.
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#' @param na_strings A character vector containing symbols to be recognized as missing values (with the exception of 0).
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#' @param zero_to_NA If \code{TRUE}, 0 will be treated as missing value.
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#' @param do_log_transformation If \code{TRUE}, the data will be log-transformed.
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#' @param log_base A numeric containing the base used, if data is log-transformed.
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#' @param use_groups If \code{TRUE}, the data contains groups.
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#' @param group_colours A character vector of hex codes for the group colors, if the data has groups. If \code{NULL}, a default color scale will be used.
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#' @param normalization A character containing the method of normalization. The possible methods are no normalization "nonorm" or "median", "loess", "quantile" or "lts" normalization.
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#' @param lts_quantile A numeric containing the quantile for the lts normalization if \code{normalization = "lts"}, default is 0.8.
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#' @param data_path \strong{character} \cr
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#' The path to an .xlsx file containing the input data.
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#' @param intensity_columns \strong{integer vector} \cr
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#' The numbers of the intensity columns in the table.
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#' @param na_strings \strong{character} \cr
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#' A vector containing the symbols to be recognized as missing values (with the exception of 0).
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#' @param zero_to_NA \strong{logical} \cr
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#' If \code{TRUE}, 0 will be treated as missing value.
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#' @param do_log_transformation \strong{logical} \cr
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#' If \code{TRUE}, the data will be log-transformed.
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#' @param log_base \strong{numeric} \cr
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#' The base used, if \code{do_log_transformation = TRUE}.
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#' @param use_groups \strong{logical} \cr
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#' If \code{TRUE}, group information encoded in the column names is used.
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#' @param group_colours \strong{character vector} \cr
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#' The hex codes for the group colors, if the data has groups. If \code{NULL}, a default color scale will be used.
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#' @param normalization \strong{character} \cr
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#' The method of normalization. Options are "nonorm" (no normalization), "median", "loess", "quantile" or "lts" normalization.
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#' @param lts_quantile \strong{numeric} \cr
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#' The quantile for the lts normalization if \code{normalization = "lts"}.
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#'
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#' @return A list containing the prepared data and the ids of the data as data.frames as well as the groups, number of groups and group colors
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#' @return A list containing the prepared data and the ids of the data as data.frames as well as the groups, number of groups and group colors.
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#' @export
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#'
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#' @examples
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#'\dontrun{
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#' path <- "/Users/thisuser/Documents/dataFolder/data.xlsx"
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#' intensity_cols <- 3:17
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#'
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#' prepared_data <- prepareData(data_path = path, intensity_columns = intensity_cols)
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#'}
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#'
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prepareData <- function (data_path,

R/workflow_QC.R

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#' The base used, if \code{do_log_transformation = TRUE}.
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#' @param groupvar_name \strong{character} \cr
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#' The name for the group variable.
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#' @param group_colours \strong{character} \cr
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#' A vector of hex codes for the group colors, if the data has groups. If \code{NULL}, a default color scale will be used.
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#' @param group_colours \strong{character vector} \cr
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#' The hex codes for the group colors, if the data has groups. If \code{NULL}, a default color scale will be used.
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### TODO: ideally, group_colours would be a named vector!
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#'
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#' @param suffix \strong{character} \cr

man/prepareData.Rd

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man/workflow_QC.Rd

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