#' Import MaxQuant files
#'
#' @inheritParams .sharedParametersAmongConverters
#' @param evidence name of 'evidence.txt' data, which includes feature-level data.
#' @param annotation name of 'annotation.txt' data which includes Raw.file, Condition, BioReplicate, Run, IsotopeLabelType information.
#' @param proteinGroups name of 'proteinGroups.txt' data. It needs to matching protein group ID. If proteinGroups=NULL, use 'Proteins' column in 'evidence.txt'.
#' @param proteinID 'Proteins'(default) or 'Leading.razor.protein' for Protein ID.
#' @param ... additional parameters to `data.table::fread`.
#'
#' @return data.frame in the MSstats required format.
#'
#' @note Warning: MSstats does not support for metabolic labeling or iTRAQ experiments.
#'
#' @author Meena Choi, Olga Vitek.
#'
#' @export
#'
#' @examples
#' mq_ev = data.table::fread(system.file("tinytest/raw_data/MaxQuant/mq_ev.csv",
#' package = "MSstatsConvert"))
#' mq_pg = data.table::fread(system.file("tinytest/raw_data/MaxQuant/mq_pg.csv",
#' package = "MSstatsConvert"))
#' annot = data.table::fread(system.file("tinytest/raw_data/MaxQuant/annotation.csv",
#' package = "MSstatsConvert"))
#' maxq_imported = MaxQtoMSstatsFormat(mq_ev, annot, mq_pg, use_log_file = FALSE)
#' head(maxq_imported)
#'
MaxQtoMSstatsFormat = function(
evidence, annotation, proteinGroups, proteinID = "Proteins",
useUniquePeptide = TRUE, summaryforMultipleRows = max,
removeFewMeasurements = TRUE, removeMpeptides = FALSE,
removeOxidationMpeptides = FALSE, removeProtein_with1Peptide = FALSE,
use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL,
...
) {
MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose,
log_file_path)
input = MSstatsConvert::MSstatsImport(list(evidence = evidence,
protein_groups = proteinGroups),
type = "MSstats",
tool = "MaxQuant", ...)
input = MSstatsConvert::MSstatsClean(input,
protein_id_col = proteinID,
remove_by_site = TRUE)
annotation = MSstatsConvert::MSstatsMakeAnnotation(input,
annotation,
"Run" = "Rawfile")
m_filter = list(col_name = "PeptideSequence",
pattern = "M",
filter = removeMpeptides,
drop_column = FALSE)
oxidation_filter = list(col_name = "Modifications",
pattern = "Oxidation",
filter = removeOxidationMpeptides,
drop_column = TRUE)
feature_columns = c("PeptideSequence", "PrecursorCharge")
input = MSstatsConvert::MSstatsPreprocess(
input,
annotation,
feature_columns,
remove_shared_peptides = useUniquePeptide,
remove_single_feature_proteins = removeProtein_with1Peptide,
pattern_filtering = list(oxidation = oxidation_filter,
m = m_filter),
feature_cleaning = list(
remove_features_with_few_measurements = removeFewMeasurements,
summarize_multiple_psms = summaryforMultipleRows),
columns_to_fill = list("FragmentIon" = NA,
"ProductCharge" = NA,
"IsotopeLabelType" = "L"))
input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns,
remove_few = removeFewMeasurements)
msg_final = paste("** Finished preprocessing. The dataset is ready",
"to be processed by the dataProcess function.")
getOption("MSstatsLog")("INFO", msg_final)
getOption("MSstatsMsg")("INFO", msg_final)
getOption("MSstatsLog")("INFO", "\n")
input
}
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