#' Import Progenesis files
#'
#' @inheritParams .sharedParametersAmongConverters
#' @param input name of Progenesis output, which is wide-format. 'Accession', 'Sequence', 'Modification', 'Charge' and one column for each run are required.
#' @param annotation name of 'annotation.txt' or 'annotation.csv' data which includes Condition, BioReplicate, Run information. It will be matched with the column name of input for MS runs.
#' @param ... additional parameters to `data.table::fread`.
#'
#' @return data.frame in the MSstats required format.
#'
#' @author Meena Choi, Olga Vitek, Ulrich Omasits
#'
#' @export
#'
#' @examples
#' progenesis_raw = system.file("tinytest/raw_data/Progenesis/progenesis_input.csv",
#' package = "MSstatsConvert")
#' annot = system.file("tinytest/raw_data/Progenesis/progenesis_annot.csv",
#' package = "MSstatsConvert")
#' progenesis_raw = data.table::fread(progenesis_raw)
#' annot = data.table::fread(annot)
#'
#' progenesis_imported = ProgenesistoMSstatsFormat(progenesis_raw, annot,
#' use_log_file = FALSE)
#' head(progenesis_imported)
#'
ProgenesistoMSstatsFormat = function(
input, annotation, useUniquePeptide = TRUE, summaryforMultipleRows = max,
removeFewMeasurements = TRUE, 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(input = input),
"MSstats", "Progenesis", ...)
input = MSstatsConvert::MSstatsClean(input,
unique(as.character(annotation$Run)),
fix_colnames = TRUE)
annotation = MSstatsConvert::MSstatsMakeAnnotation(input, annotation)
oxidation_filter = list(col_name = "PeptideSequence",
pattern = "Oxidation",
filter = removeOxidationMpeptides,
drop_column = FALSE)
feature_columns = c("PeptideSequence", "PrecursorCharge")
input = MSstatsConvert::MSstatsPreprocess(
input,
annotation,
feature_columns,
remove_shared_peptides = useUniquePeptide,
remove_single_feature_proteins = removeProtein_with1Peptide,
feature_cleaning = list(
remove_features_with_few_measurements = removeFewMeasurements,
summarize_multiple_psms = summaryforMultipleRows),
pattern_filtering = list(oxidation = oxidation_filter),
columns_to_fill = list("FragmentIon" = NA,
"ProductCharge" = NA,
"IsotopeLabelType" = "L"))
input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns,
remove_few = removeFewMeasurements)
data.table::setnames(input, "PeptideSequence", "PeptideModifiedSequence",
skip_absent = TRUE)
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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