## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----logs--------------------------------------------------------------------- library(MSstatsConvert) # default - creates a new file MSstatsLogsSettings(use_log_file = TRUE, append = FALSE) # default - creates a new file MSstatsLogsSettings(use_log_file = TRUE, append = TRUE, log_file_path = "log_file.log") # switches logging off MSstatsLogsSettings(use_log_file = FALSE, append = FALSE) # switches off logs and messages MSstatsLogsSettings(use_log_file = FALSE, verbose = FALSE) ## ----------------------------------------------------------------------------- MSstatsSaveSessionInfo() ## ----------------------------------------------------------------------------- maxquant_evidence = read.csv(system.file("tinytest/raw_data/MaxQuant/mq_ev.csv", package = "MSstatsConvert")) maxquant_proteins = read.csv(system.file("tinytest/raw_data/MaxQuant/mq_pg.csv", package = "MSstatsConvert")) maxquant_imported = MSstatsImport(list(evidence = maxquant_evidence, protein_groups = maxquant_proteins), type = "MSstats", tool = "MaxQuant") is(maxquant_imported) openms_input = read.csv(system.file( "tinytest/raw_data/OpenMSTMT/openmstmt_input.csv", package = "MSstatsConvert" )) openms_imported = MSstatsImport(list(input = openms_input), "MSstatsTMT", "OpenMS") is(openms_imported) ## ----------------------------------------------------------------------------- getInputFile(maxquant_imported, "evidence")[1:5, 1:5] ## ----------------------------------------------------------------------------- maxquant_cleaned = MSstatsClean(maxquant_imported, protein_id_col = "Proteins") head(maxquant_cleaned) openms_cleaned = MSstatsClean(openms_imported) head(openms_cleaned) ## ----------------------------------------------------------------------------- maxquant_annotation = read.csv(system.file( "tinytest/raw_data/MaxQuant/annotation.csv", package = "MSstatsConvert" )) maxquant_annotation = MSstatsMakeAnnotation(maxquant_cleaned, maxquant_annotation, Run = "Rawfile") m_filter = list(col_name = "PeptideSequence", pattern = "M", filter = TRUE, drop_column = FALSE) oxidation_filter = list(col_name = "Modifications", pattern = "Oxidation", filter = TRUE, drop_column = TRUE) feature_columns = c("PeptideSequence", "PrecursorCharge") maxquant_processed = MSstatsPreprocess( maxquant_cleaned, maxquant_annotation, feature_columns, remove_shared_peptides = TRUE, remove_single_feature_proteins = FALSE, pattern_filtering = list(oxidation = oxidation_filter, m = m_filter), feature_cleaning = list(remove_features_with_few_measurements = TRUE, summarize_multiple_psms = max), columns_to_fill = list("FragmentIon" = NA, "ProductCharge" = NA, "IsotopeLabelType" = "L")) head(maxquant_processed) # OpenMS - TMT data feature_columns_tmt = c("PeptideSequence", "PrecursorCharge") openms_processed = MSstatsPreprocess( openms_cleaned, NULL, feature_columns_tmt, remove_shared_peptides = TRUE, remove_single_feature_proteins = TRUE, feature_cleaning = list(remove_features_with_few_measurements = TRUE, summarize_multiple_psms = max) ) head(openms_processed) ## ---- eval = FALSE------------------------------------------------------------ # list( # list(score_column = "Intensity", score_threshold = 1, # direction = "greater", behavior = "remove", # handle_na = "remove", fill_value = NA, filter = TRUE, drop = FALSE # ) # ) ## ----------------------------------------------------------------------------- maxquant_balanced = MSstatsBalancedDesign(maxquant_processed, feature_columns) head(maxquant_balanced) dim(maxquant_balanced) dim(maxquant_processed) openms_balanced = MSstatsBalancedDesign(openms_processed, feature_columns_tmt) head(openms_balanced) dim(openms_balanced) dim(openms_processed)