From c24db6b46698ef49725b062a0624fbd14cd84e6e Mon Sep 17 00:00:00 2001 From: tonywu1999 Date: Thu, 9 Apr 2026 17:00:15 -0400 Subject: [PATCH 1/5] refactor(tmt-converters): Move MSstatsTMT converters into MSstatsConvert --- R/converters_MaxQtoMSstatsTMTFormat.R | 68 ++++++++ R/converters_OpenMStoMSstatsTMTFormat.R | 53 ++++++ R/converters_PDtoMSstatsTMTFormat.R | 67 ++++++++ R/converters_PhilosophertoMSstatsTMTFormat.R | 121 ++++++++++++++ R/converters_SpectroMinetoMSstatsTMTFormat.R | 81 ++++++++++ .../raw_data/MaxQuantTMT/mq_annotation.csv | 151 ++++++++++++++++++ .../tinytest/raw_data/PDTMT/pd_annotation.csv | 151 ++++++++++++++++++ .../Philosopher/MSstatsTMT_annotation.csv | 61 +++++++ .../tinytest/raw_data/Philosopher/msstats.csv | 95 +++++++++++ .../SpectroMine/spectromine_annotation.csv | 73 +++++++++ inst/tinytest/test_converters_tmt.R | 43 +++++ 11 files changed, 964 insertions(+) create mode 100644 R/converters_MaxQtoMSstatsTMTFormat.R create mode 100644 R/converters_OpenMStoMSstatsTMTFormat.R create mode 100644 R/converters_PDtoMSstatsTMTFormat.R create mode 100644 R/converters_PhilosophertoMSstatsTMTFormat.R create mode 100644 R/converters_SpectroMinetoMSstatsTMTFormat.R create mode 100644 inst/tinytest/raw_data/MaxQuantTMT/mq_annotation.csv create mode 100644 inst/tinytest/raw_data/PDTMT/pd_annotation.csv create mode 100644 inst/tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv create mode 100644 inst/tinytest/raw_data/Philosopher/msstats.csv create mode 100644 inst/tinytest/raw_data/SpectroMine/spectromine_annotation.csv create mode 100644 inst/tinytest/test_converters_tmt.R diff --git a/R/converters_MaxQtoMSstatsTMTFormat.R b/R/converters_MaxQtoMSstatsTMTFormat.R new file mode 100644 index 000000000..efb925437 --- /dev/null +++ b/R/converters_MaxQtoMSstatsTMTFormat.R @@ -0,0 +1,68 @@ +#' Generate MSstatsTMT required input format from MaxQuant output +#' +#' @param evidence name of 'evidence.txt' data, which includes feature-level data. +#' @param proteinGroups name of 'proteinGroups.txt' data. +#' @param annotation data frame which contains column Run, Fraction, TechRepMixture, Mixture, Channel, BioReplicate, Condition. Refer to the example 'annotation.mq' for the meaning of each column. +#' @param which.proteinid Use 'Proteins' (default) column for protein name. 'Leading.proteins' or 'Leading.razor.proteins' or 'Gene.names' can be used instead to get the protein ID with single protein. However, those can potentially have the shared peptides. +#' @param rmProt_Only.identified.by.site TRUE will remove proteins with '+' in 'Only.identified.by.site' column from proteinGroups.txt, which was identified only by a modification site. FALSE is the default. +#' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param ... additional parameters to `data.table::fread`. +#' @inheritParams .sharedParametersAmongConverters +#' +#' @return data.frame of class "MSstatsTMT" +#' +#' @export +#' +#' @examples +#' evidence = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_ev.csv", +#' package = "MSstatsConvert")) +#' proteinGroups = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_pg.csv", +#' package = "MSstatsConvert")) +#' annotation.mq = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_annotation.csv", +#' package = "MSstatsConvert")) +#' input.mq <- MaxQtoMSstatsTMTFormat(evidence, proteinGroups, annotation.mq) +#' head(input.mq) +#' +MaxQtoMSstatsTMTFormat = function( + evidence, proteinGroups, annotation, which.proteinid = 'Proteins', + rmProt_Only.identified.by.site = FALSE, useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL, + ... +) { + MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose, + log_file_path, + base = "MSstatsTMT_converter_log_") + + input = MSstatsConvert::MSstatsImport(list(evidence = evidence, + protein_groups = proteinGroups), + "MSstatsTMT", "MaxQuant", ...) + input = MSstatsConvert::MSstatsClean( + input, + protein_id_col = which.proteinid, + remove_by_site = rmProt_Only.identified.by.site, + channel_columns = "Reporterintensitycorrected") + annotation = MSstatsConvert::MSstatsMakeAnnotation(input, annotation) + + feature_columns = c("PeptideSequence", "PrecursorCharge") + input = MSstatsConvert::MSstatsPreprocess( + input, + annotation, + feature_columns, + remove_shared_peptides = useUniquePeptide, + remove_single_feature_proteins = rmProtein_with1Feature, + feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, + summarize_multiple_psms = summaryforMultipleRows)) + input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns, + fix_missing = "zero_to_na") + data.table::setnames(input, "PrecursorCharge", "Charge", skip_absent = TRUE) + + msg_final = paste("** Finished preprocessing. The dataset is ready", + "to be processed by the proteinSummarization function.") + getOption("MSstatsLog")("INFO", msg_final) + getOption("MSstatsMsg")("INFO", msg_final) + getOption("MSstatsLog")("INFO", "\n") + input +} \ No newline at end of file diff --git a/R/converters_OpenMStoMSstatsTMTFormat.R b/R/converters_OpenMStoMSstatsTMTFormat.R new file mode 100644 index 000000000..8c4f0f8e6 --- /dev/null +++ b/R/converters_OpenMStoMSstatsTMTFormat.R @@ -0,0 +1,53 @@ +#' Generate MSstatsTMT required input format for OpenMS output +#' @param input MSstatsTMT report from OpenMS +#' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param summaryforMultiplePSMs sum(default) or max - when there are multiple measurements for certain feature in certain run, select the feature with the largest summation or maximal value. +#' @param ... additional parameters to `data.table::fread`. +#' @inheritParams .sharedParametersAmongConverters +#' +#' @return `data.frame` of class `MSstatsTMT`. +#' +#' @export +#' +#' @examples +#' raw.om = data.table::fread(system.file("tinytest/raw_data/OpenMSTMT/openmstmt_input.csv", +#' package = "MSstatsConvert")) +#' input.om <- OpenMStoMSstatsTMTFormat(raw.om) +#' head(input.om) +#' +OpenMStoMSstatsTMTFormat = function( + input, useUniquePeptide = TRUE, rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, summaryforMultiplePSMs = sum, + use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL, ... +) { + MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose, + log_file_path, + base = "MSstatsTMT_converter_log_") + + input = MSstatsConvert::MSstatsImport(list(input = input), + "MSstatsTMT", "OpenMS", ...) + input = MSstatsConvert::MSstatsClean(input) + + feature_columns = c("PeptideSequence", "PrecursorCharge") + input = MSstatsConvert::MSstatsPreprocess( + input, + NULL, + feature_columns, + remove_shared_peptides = useUniquePeptide, + remove_single_feature_proteins = rmProtein_with1Feature, + feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, + summarize_multiple_psms = summaryforMultiplePSMs) + ) + input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns, + fix_missing = "zero_to_na") + + data.table::setnames(input, "PrecursorCharge", "Charge", skip_absent = TRUE) + + msg_final = paste("** Finished preprocessing. The dataset is ready", + "to be processed by the proteinSummarization function.") + getOption("MSstatsLog")("INFO", msg_final) + getOption("MSstatsMsg")("INFO", msg_final) + getOption("MSstatsLog")("INFO", "\n") + input +} \ No newline at end of file diff --git a/R/converters_PDtoMSstatsTMTFormat.R b/R/converters_PDtoMSstatsTMTFormat.R new file mode 100644 index 000000000..b5bad061d --- /dev/null +++ b/R/converters_PDtoMSstatsTMTFormat.R @@ -0,0 +1,67 @@ +#' Convert Proteome Discoverer output to MSstatsTMT format. +#' +#' @param input PD report or a path to it. +#' @param annotation annotation with Run, Fraction, TechRepMixture, Mixture, Channel, +#' BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column. +#' @param which.proteinid Use 'Protein.Accessions'(default) column for protein name. 'Master.Protein.Accessions' can be used instead to get the protein name with single protein. +#' @param useNumProteinsColumn logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet. +#' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param ... additional parameters to `data.table::fread`. +#' @inheritParams .sharedParametersAmongConverters +#' +#' @return `data.frame` of class `MSstatsTMT` +#' +#' @export +#' +#' @examples +#' raw.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pdtmt_input.csv", +#' package = "MSstatsConvert")) +#' annotation.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annotation.csv", +#' package = "MSstatsConvert")) +#' head(raw.pd) +#' head(annotation.pd) +#' input.pd <- PDtoMSstatsTMTFormat(raw.pd, annotation.pd) +#' head(input.pd) +#' +PDtoMSstatsTMTFormat <- function( + input, annotation, which.proteinid = 'Protein.Accessions', + useNumProteinsColumn = TRUE, useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL, ... +) { + MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose, + log_file_path, + base = "MSstatsTMT_converter_log_") + + input = MSstatsConvert::MSstatsImport(list(input = input), + "MSstatsTMT", "ProteomeDiscoverer", ...) + input = MSstatsConvert::MSstatsClean( + input, + protein_id_column = which.proteinid, + remove_shared = useNumProteinsColumn, + remove_protein_groups = useNumProteinsColumn) + annotation = MSstatsConvert::MSstatsMakeAnnotation(input, annotation) + + feature_columns = c("PeptideSequence", "PrecursorCharge") + input = MSstatsConvert::MSstatsPreprocess( + input, + annotation, + feature_columns = c("PeptideSequence", "PrecursorCharge"), + remove_shared_peptides = useUniquePeptide, + remove_single_feature_proteins = rmProtein_with1Feature, + feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, + summarize_multiple_psms = summaryforMultipleRows) + ) + input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns, + fix_missing = "zero_to_na") + data.table::setnames(input, "PrecursorCharge", "Charge", skip_absent = TRUE) + + msg_final = paste("** Finished preprocessing. The dataset is ready", + "to be processed by the proteinSummarization function.") + getOption("MSstatsLog")("INFO", msg_final) + getOption("MSstatsMsg")("INFO", msg_final) + getOption("MSstatsLog")("INFO", "\n") + input +} \ No newline at end of file diff --git a/R/converters_PhilosophertoMSstatsTMTFormat.R b/R/converters_PhilosophertoMSstatsTMTFormat.R new file mode 100644 index 000000000..9e5158002 --- /dev/null +++ b/R/converters_PhilosophertoMSstatsTMTFormat.R @@ -0,0 +1,121 @@ +#' Convert Philosopher (Fragpipe) output to MSstatsTMT format. +#' +#' @param input data.frame of `msstats.csv` file produced by Philosopher +#' @param annotation annotation with Run, Fraction, TechRepMixture, Mixture, Channel, +#' BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column. Channel column should be +#' consistent with the channel columns (Ignore the prefix "Channel ") in msstats.csv file. Run column should be consistent with the Spectrum.File columns in msstats.csv file. +#' @param protein_id_col Use 'Protein'(default) column for protein name. +#' 'Master.Protein.Accessions' can be used instead to get the protein ID with single protein. +#' @param peptide_id_col Use 'Peptide.Sequence'(default) column for peptide sequence. +#' 'Modified.Peptide.Sequence' can be used instead to get the modified peptide sequence. +#' @param Purity_cutoff Cutoff for purity. Default is 0.6 +#' @param PeptideProphet_prob_cutoff Cutoff for the peptide identification probability. Default is 0.7. +#' The probability is confidence score determined by PeptideProphet and higher values indicate greater confidence. +#' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. +#' @param rmPeptide_OxidationM TRUE (default) will remove the peptides including oxidation (M) sequence. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param ... additional parameters to `data.table::fread`. +#' @inheritParams .sharedParametersAmongConverters +#' +#' @return `data.frame` of class `MSstatsTMT` +#' +#' @examples +#' input_file_path = system.file("tinytest/raw_data/Philosopher/msstats.csv", +#' package = "MSstatsTMT") +#' annotation_file_path = system.file("tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv", +#' package = "MSstatsTMT") +#' input = data.table::fread(input_file_path) +#' annotation = data.table::fread(annotation_file_path) +#' msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) +#' head(msstats_format) +#' +#' @export +PhilosophertoMSstatsTMTFormat = function( + input, annotation, protein_id_col = "Protein", + peptide_id_col = "Peptide.Sequence", Purity_cutoff = 0.6, + PeptideProphet_prob_cutoff = 0.7, useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, rmPeptide_OxidationM = TRUE, + rmProtein_with1Feature = FALSE, summaryforMultipleRows = sum, + use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL, ... +) { + MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose, + log_file_path, + base = "MSstatsTMT_converter_log_") + checkmate::assertTRUE(!is.null(input)) + + input[["Is.Unique"]] = as.logical(input[["Is.Unique"]]) + mixture_files = list(Mixture1=data.table(input)) + + input = MSstatsConvert::MSstatsImport(c(mixture_files, + list(annotation = annotation)), + type = "MSstatsTMT", + tool = "Philosopher") + channels = unique(annotation[["Channel"]]) + input = MSstatsConvert::MSstatsClean(input, protein_id_col, peptide_id_col, + channels, useUniquePeptide) + annotation = MSstatsMakeAnnotation(input, annotation) + + purity_filter = list(score_column = "Purity", + score_threshold = Purity_cutoff, + direction = "greater", + behavior = "remove", + handle_na = "keep", + fill_value = NULL, + filter = TRUE, + drop_column = FALSE) + probability_filter = list(score_column = "PeptideProphetProbability", + score_threshold = PeptideProphet_prob_cutoff, + direction = "greater", + behavior = "remove", + handle_na = "keep", + fill_value = NULL, + filter = TRUE, + drop_column = FALSE) + oxidation_filter = list(col_name = "PeptideSequence", + pattern = "Oxidation", + filter = rmPeptide_OxidationM, + drop_column = FALSE) + + feature_columns = c("PeptideSequence", "PrecursorCharge") + input = MSstatsPreprocess( + input, + annotation, + feature_columns, + remove_shared_peptides = useUniquePeptide, + remove_single_feature_proteins = rmProtein_with1Feature, + score_filtering = list(pur = purity_filter, prob = probability_filter), + pattern_filtering = list(ox = oxidation_filter), + feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, + summarize_multiple_psms = summaryforMultipleRows) + ) + input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns, + fix_missing = "zero_to_na") + data.table::setnames(input, "PrecursorCharge", "Charge", skip_absent = TRUE) + + msg_final = paste("** Finished preprocessing. The dataset is ready", + "to be processed by the proteinSummarization function.") + getOption("MSstatsLog")("INFO", msg_final) + getOption("MSstatsMsg")("INFO", msg_final) + getOption("MSstatsLog")("INFO", "\n") + input +} + + +#' Convert Philosopher parameters to consistent format +#' @inheritParams PhilosophertoMSstatsTMTFormat +#' @keywords internal +.getPhilosopherInput = function(input, path, folder) { + if (!is.null(input)) { + mixture_files = input + } else { + if (folder) { + mixture_files = list.files(path, pattern = "msstats", + full.names = TRUE) + } else { + mixture_files = path + } + } + mixture_files = as.list(mixture_files) + names(mixture_files) = paste0("Mixture", seq_along(mixture_files)) + mixture_files +} diff --git a/R/converters_SpectroMinetoMSstatsTMTFormat.R b/R/converters_SpectroMinetoMSstatsTMTFormat.R new file mode 100644 index 000000000..cc2ec2bb3 --- /dev/null +++ b/R/converters_SpectroMinetoMSstatsTMTFormat.R @@ -0,0 +1,81 @@ +#' Import data from SpectroMine +#' +#' @param input data name of SpectroMine PSM output. Read PSM sheet. +#' @param annotation data frame which contains column Run, Fraction, TechRepMixture, Mixture, Channel, BioReplicate, Condition. Refer to the example 'annotation.mine' for the meaning of each column. +#' @param filter_with_Qvalue TRUE(default) will filter out the intensities that have greater than qvalue_cutoff in EG.Qvalue column. Those intensities will be replaced with NA and will be considered as censored missing values for imputation purpose. +#' @param qvalue_cutoff Cutoff for EG.Qvalue. default is 0.01. +#' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param ... additional parameters to `data.table::fread`. +#' @inheritParams .sharedParametersAmongConverters +#' +#' @return `data.frame` of class `MSstatsTMT` +#' +#' @export +#' @examples +#' raw.mine = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_input.csv", +#' package = "MSstatsConvert")) +#' annotation.mine = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_annotation.csv", +#' package = "MSstatsConvert")) +#' head(raw.mine) +#' head(annotation.mine) +#' input.mine <- SpectroMinetoMSstatsTMTFormat(raw.mine, annotation.mine) +#' head(input.mine) +#' +SpectroMinetoMSstatsTMTFormat <- function( + input, annotation, filter_with_Qvalue = TRUE, qvalue_cutoff = 0.01, + useUniquePeptide = TRUE, rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, summaryforMultipleRows = sum, + use_log_file = TRUE, append = FALSE, verbose = TRUE, log_file_path = NULL, ... +) { + MSstatsConvert::MSstatsLogsSettings(use_log_file, append, verbose, + log_file_path, + base = "MSstatsTMT_converter_log_") + + input = MSstatsConvert::MSstatsImport(list(input = input), + "MSstatsTMT", "SpectroMine", ...) + input = MSstatsConvert::MSstatsClean(input) + annotation = MSstatsMakeAnnotation(input, annotation) + + pq_filter = list(score_column = "PGQValue", + score_threshold = 0.01, + direction = "smaller", + behavior = "fill", + handle_na = "keep", + fill_value = NA, + filter = TRUE, + drop_column = TRUE) + + qval_filter = list(score_column = "Qvalue", + score_threshold = qvalue_cutoff, + direction = "smaller", + behavior = "fill", + handle_na = "keep", + fill_value = NA, + filter = filter_with_Qvalue, + drop_column = TRUE) + + feature_columns = c("PeptideSequence", "PrecursorCharge") + input = MSstatsConvert::MSstatsPreprocess( + input, + annotation, + feature_columns, + remove_shared_peptides = useUniquePeptide, + remove_single_feature_proteins = rmProtein_with1Feature, + score_filtering = list(pgq = pq_filter, psm_q = qval_filter), + feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, + summarize_multiple_psms = summaryforMultipleRows) + ) + input = MSstatsConvert::MSstatsBalancedDesign(input, feature_columns, + fix_missing = "zero_to_na") + data.table::setnames(input, "PrecursorCharge", "Charge", skip_absent = TRUE) + + msg_final = paste("** Finished preprocessing. The dataset is ready", + "to be processed by the proteinSummarization function.") + getOption("MSstatsLog")("INFO", msg_final) + getOption("MSstatsMsg")("INFO", msg_final) + getOption("MSstatsLog")("INFO", "\n") + input +} + + diff --git a/inst/tinytest/raw_data/MaxQuantTMT/mq_annotation.csv b/inst/tinytest/raw_data/MaxQuantTMT/mq_annotation.csv new file mode 100644 index 000000000..b2fccdb74 --- /dev/null +++ b/inst/tinytest/raw_data/MaxQuantTMT/mq_annotation.csv @@ -0,0 +1,151 @@ +"Run","Fraction","TechRepMixture","Channel","Condition","Mixture","BioReplicate" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.0","Norm","Mixture1","Norm" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.1","0.667","Mixture1","0.667" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.2","0.125","Mixture1","0.125" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.3","0.5","Mixture1","0.5" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.4","1","Mixture1","1" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.5","0.125","Mixture1","0.125" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.6","0.5","Mixture1","0.5" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.7","1","Mixture1","1" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.8","0.667","Mixture1","0.667" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_01","1","1","channel.9","Norm","Mixture1","Norm" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_02","1","2","channel.0","Norm","Mixture1","Norm" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_02","1","2","channel.1","0.667","Mixture1","0.667" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_02","1","2","channel.2","0.125","Mixture1","0.125" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_02","1","2","channel.3","0.5","Mixture1","0.5" +"161117_SILAC_HeLa_UPS1_TMT10_Mixture1_02","1","2","channel.4","1","Mixture1","1" 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+16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01,1,1,plex16,129C,CPT0014450004_T,T +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f02,2,1,plex16,129C,CPT0014450004_T,T +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f03,3,1,plex16,129C,CPT0014450004_T,T +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01,1,1,plex16,130N,CPT0088570001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f02,2,1,plex16,130N,CPT0088570001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f03,3,1,plex16,130N,CPT0088570001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01,1,1,plex16,130C,CPT0014470001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f02,2,1,plex16,130C,CPT0014470001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f03,3,1,plex16,130C,CPT0014470001_N,N +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01,1,1,plex16,131N,pool16_NORM,Norm +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f02,2,1,plex16,131N,pool16_NORM,Norm +16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f03,3,1,plex16,131N,pool16_NORM,Norm +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,126,CPT0006730001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,126,CPT0006730001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,126,CPT0006730001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,127N,CPT0069190001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,127N,CPT0069190001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,127N,CPT0069190001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,127C,CPT0092730003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,127C,CPT0092730003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,127C,CPT0092730003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,128N,CPT0092740003_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,128N,CPT0092740003_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,128N,CPT0092740003_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,128C,QC7_QC,QC +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,128C,QC7_QC,QC +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,128C,QC7_QC,QC +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,129N,CPT0006630003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,129N,CPT0006630003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,129N,CPT0006630003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,129C,CPT0025920001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,129C,CPT0025920001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,129C,CPT0025920001_N,N +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,130N,CPT0025880003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,130N,CPT0025880003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,130N,CPT0025880003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,130C,CPT0069160003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,130C,CPT0069160003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,130C,CPT0069160003_T,T +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01,1,1,plex17,131N,pool17_NORM,Norm +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f02,2,1,plex17,131N,pool17_NORM,Norm +17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f03,3,1,plex17,131N,pool17_NORM,Norm \ No newline at end of file diff --git a/inst/tinytest/raw_data/Philosopher/msstats.csv b/inst/tinytest/raw_data/Philosopher/msstats.csv new file mode 100644 index 000000000..21795e2f5 --- /dev/null +++ b/inst/tinytest/raw_data/Philosopher/msstats.csv @@ -0,0 +1,95 @@ +"Spectrum.Name","Spectrum.File","Peptide.Sequence","Modified.Peptide.Sequence","Probability","Charge","Protein.Start","Protein.End","Gene","Mapped.Genes","Protein","Protein.ID","Mapped.Proteins","Protein.Description","Is.Unique","Purity","Intensity","Channel.126","Channel.127N","Channel.127C","Channel.128N","Channel.128C","Channel.129N","Channel.129C","Channel.130N","Channel.130C","Channel.131N" +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.04225.04225.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","SSDGGSEEPPDRR","n[230]SSDGGSEEPPDRR",1,3,21,33,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,0.5,29058558,53473.1016,66971.8594,27558.7285,66180.9219,94775.4531,72129.5234,93412.9375,52533.7422,58089.5234,44198.957 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.05945.05945.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","MDDSDQDSCR","n[230]MDDSDQDSCR",1,2,198,207,"PAX8","","sp|Q06710|PAX8_HUMAN","Q06710","","Paired box protein",TRUE,1,64983984,133589.7656,277471.9688,339930.8125,458741,27250.6348,599682,374046.5,396600.1562,288080.5625,243704.3906 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.07087.07087.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","AEAEAEAGSPRPDPR","n[230]AEAEAEAGSPRPDPR",1,3,4637,4651,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,65230552,324756.4688,18408.9414,127025.6328,16732.8223,30560.0566,22088.2109,234934.5938,99157,117041.4609,88308.0156 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.07988.07988.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","QDGDYSPDNSAQPGDR","n[230]QDGDYSPDNSAQPGDR",1,2,309,324,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,134390016,62969.4297,68964.1328,292931.4375,112034.7734,33149.5703,53302.7773,90751.3359,231425.7344,268154.9375,173834.125 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.08116.08116.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","QDGDYSPDNSAQPGDR","n[230]QDGDYSPDNSAQPGDR",1,2,309,324,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,149889712,131517.6562,80017.8438,272977.5938,151596.1875,68935.0391,71528.5312,91335.1562,207628.3906,256628.2969,215388.0781 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.10882.10882.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","EGQGEGETQEAAAATAAAR","n[230]EGQGEGETQEAAAATAAAR",1,3,3681,3699,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0.67,48511452,194037.7812,24009.9629,82478.3828,57474.3984,71291.9922,63427.7773,164748.5625,116056.3984,84174.4219,71237.1328 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.11114.11114.4","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","QTSDGNWLMVHR","n[230]QTS[316]DGNWLM[147]VHR",0.9993,4,168,179,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,0.74,34173808,178713.8594,179251.4688,138970.8125,189085.2188,146196.4531,231841.9062,233118.375,177988.6562,171249.7969,137565.25 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.14116.14116.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LTMLNTVSK","n[230]LTM[147]LNTVSK",0.9157,3,68,76,"SH3GL1","","sp|Q99961|SH3G1_HUMAN","Q99961","","Endophilin-A2",TRUE,1,98872056,419643.4062,395606.6875,286063.0625,292227.6562,596860.1875,241903.7812,688371.25,352771.9375,357452,347223.0938 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.14145.14145.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","ESTESSNTTIEDEDVK","n[230]ESTESSNTTIEDEDVK",1,3,329,344,"CAMK2D","","sp|Q13557|KCC2D_HUMAN","Q13557","","Calcium/calmodulin-dependent protein kinase type II subunit delta",TRUE,1,289236352,124410.7422,121518.8047,152290.9375,149399.6562,216064.2969,825769.25,196175.1875,199284.9531,209662.1562,141410.4375 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.14393.14393.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","ESTESSNTTIEDEDVK","n[230]ESTESSNTTIEDEDVK",1,3,329,344,"CAMK2D","","sp|Q13557|KCC2D_HUMAN","Q13557","","Calcium/calmodulin-dependent protein kinase type II subunit delta",TRUE,0.76,229207472,70812,71602.7891,86021.3984,87021.6875,104304.7969,389823,98218.8047,111910.8359,112847.5938,82529.75 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.14625.14625.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","YQQETSVSQLPGRPK","n[230]YQQETSVSQLPGRPK",1,3,1564,1578,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,1,28733976,162676.0156,163120.3125,136647.4844,186262.5781,288684.6562,190590.3125,258702.3438,162000.1719,160732.6875,166368.1094 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.14901.14901.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","GAILTTMLATR","n[230]GAILTTM[147]LATR",0.9999,3,302,312,"CAMK2D","CAMK2A;CAMK2B","sp|Q13557|KCC2D_HUMAN","Q13557","sp|Q13554|KCC2B_HUMAN;sp|Q9UQM7|KCC2A_HUMAN","Calcium/calmodulin-dependent protein kinase type II subunit delta",FALSE,1,40487512,87156.6953,123929.8359,136017.3125,113796.1328,325175.4062,204953.2969,183429.3438,175068,133387.4844,120227.0469 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.15525.15525.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","ALETMNK","n[230]ALETMNK",0.994,2,157,163,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,32466892,208282.125,533066.25,294146.9062,563202.25,460770.9375,823593.25,570828.875,537096.9375,312645.3438,404656.75 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.17357.17357.4","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","KGGDGIKPPPIIGR","n[230]KGGDGIKPPPIIGR",1,4,5,18,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,909555584,166787.9062,270603.9062,255155.9844,254222.8438,258203.4531,233064.1406,280672.3125,311485.6875,324233.6875,275042.7188 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.18897.18897.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","SSLYCSDIGK","n[230]SSLYCSDIGK",1,2,379,388,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,322046880,364898.125,424766.8125,1384306,574772.625,287451.5625,273002.1875,449773.7812,788061.625,1179433,859890.6875 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.19684.19684.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","GCGVVEFK","n[230]GCGVVEFK",0.9999,2,142,149,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,0.82,207355840,442496.6562,487739.3125,484301.2188,803611.875,281926.2812,1078799,718019.6875,721879.5,705089.3125,622555.375 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.21444.21444.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","YLEANMTQSALPK","n[230]YLEANM[147]TQSALPK",1,2,282,294,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,26254800,116355.8203,137655.3438,139374.0781,126379.3984,133682.4375,153402.6562,155367.5469,164374.6562,175618.3594,148088.8125 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.25901.25901.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NIGNTFFK","n[230]NIGNTFFK",1,2,228,235,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,1,376800160,2421456.75,1371379.25,3077288.75,1682978.25,3848730.75,4906989,2402642.75,3504737.75,3080020.25,2810615 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.28250.28250.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LYGPTNFSPIINHVAR","n[230]LYGPTNFSPIINHVAR",1,3,391,406,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,0.54,455828640,114046.5234,148080.125,141590.0938,121584.5938,145680.7656,177571.0938,193098.9844,172152.4531,169095.2031,142382.5781 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.28315.28315.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LYGPTNFSPIINHVAR","n[230]LYGPTNFSPIINHVAR",1,2,391,406,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,1,36354812,131424.2031,176060.875,141853.5625,130879.4219,136574.2188,210731.9219,243962.1875,172536.0781,167103.6094,133787.7344 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.28349.28349.6","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LVGRPPLPVPAVGIGTVHLHQHEDILAK","n[230]LVGRPPLPVPAVGIGTVHLHQHEDILAK",1,6,889,916,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,63040900,100460.5078,99387.3672,214580.3594,101788.9766,58616.668,88769.5547,110691.8438,183040.7344,199704.375,135561.6719 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.28377.28377.5","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LVGRPPLPVPAVGIGTVHLHQHEDILAK","n[230]LVGRPPLPVPAVGIGTVHLHQHEDILAK",1,5,889,916,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,0.37,48322436,145621.6562,147147.1875,273589.5625,172246.8281,142203.9688,411355.625,192515.2969,249207.5781,266824.125,210832.5156 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.28533.28533.5","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","LVGRPPLPVPAVGIGTVHLHQHEDILAK","n[230]LVGRPPLPVPAVGIGTVHLHQHEDILAK",1,5,889,916,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,60786052,104359.125,98972.8203,257540.7969,136414.8281,64393.293,178737.9375,120276.2578,212543.3125,225913.1875,168611.0781 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.34349.34349.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VFISNIPYDMK","n[230]VFISNIPYDMK",1,2,102,112,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,135656624,141339.875,168169.3281,192865.7344,290690.75,68942.9531,515769.2188,470512.0938,255537.8438,240030.5156,203183.7969 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.34351.34351.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VFISNIPYDMK","n[230]VFISNIPYDMK",1,2,102,112,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,141525264,187644.5781,211548.6406,237330.9844,377179.9375,67541.7344,600410.5625,550691.5,280020.7812,260654.5312,233607.5938 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.34531.34531.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VFFDVDIGGER","n[230]VFFDVDIGGER",1,2,18,28,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,1,61006892,495034.5312,386296.7188,616756.5625,321886.5312,568345.25,712595.5625,595983.4375,633466.3125,564178.3125,559268.8125 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.34545.34545.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VFFDVDIGGER","n[230]VFFDVDIGGER",1,2,18,28,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,0.85,133909016,516421.2188,413345.4688,677029.875,362656.0312,699778.0625,853199,621233.75,752521.0625,637508,632195.3125 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.36974.36974.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NLPFDLTWQK","n[230]NLPFDLTWQK",1,2,529,538,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,95639424,193262.8594,201530.3125,233439.0625,348824.0312,59749.125,570347.375,532727.5,275453.4062,241193,213682.25 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.37048.37048.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NLPFDLTWQK","n[230]NLPFDLTWQK",1,3,529,538,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,58497004,451318.5938,182573.125,233350.5469,393898.3438,71178.7734,611627.875,505575.3438,250232.9062,258799.3594,424330.2812 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.38089.38089.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,3,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0.46,476562400,252029.7969,364502.8438,335493.5312,326679.8438,345861.8438,298383.1875,345714.875,394625.875,394398.7188,338799.6875 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.38628.38628.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,3,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,25428448,61291.4375,74236.0938,74793.1719,70132.7344,86858.2422,84709.7734,78207.6562,90386.7812,81704.6797,77328.6953 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.38674.38674.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,3,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0,28157016,58978.7656,93921.3906,81770.9609,72799.4375,100891.75,87043.7891,92984.625,103720.1719,89025.9297,89494.5312 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.39183.39183.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,3,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0.51,11338453,68699.5469,112747.4609,94652.0469,85027.4844,122260.9219,97572.8906,124826.6797,134252.0469,103595.9766,99187.1328 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.39554.39554.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",0.9951,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0.72,88392712,139607.5156,144368.6562,139572.2031,206676.2969,180988.375,195630.7031,206411.4688,190020.9375,158484.1875,153422.9375 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.39907.39907.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","AVPVWDVLASGYVSR","n[230]AVPVWDVLASGYVSR",1,2,2533,2547,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,299018944,260604.5312,91985.125,115962.3594,100326.4375,131405.6719,185918.7344,207543.0781,144858.0938,124957.3594,123795.7578 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.39927.39927.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","AVPVWDVLASGYVSR","n[230]AVPVWDVLASGYVSR",1,3,2533,2547,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0.64,330016224,91648.2734,32969.4844,49777.0156,28548.3887,41787.3242,42108.5586,83213.7188,51249.25,52722.7188,51162.3242 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.40654.40654.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,2,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,11922556,32318.0098,40199.4727,48802.3125,79679.25,19577.9219,135823.5312,139380.5625,63022.6055,60150.9727,52114.4062 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.40656.40656.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","AVPVWDVLASGYVSGAAR","n[230]AVPVWDVLASGYVSGAAR",1,3,4670,4687,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,23206878,27124.5215,31872.9922,30046.9648,29435.6699,36784.6758,43625.1875,32007.9844,38299.5664,31733.7734,33042.3867 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.40681.40681.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","AVPVWDVLASGYVSGAAR","n[230]AVPVWDVLASGYVSGAAR",1,3,4670,4687,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0.5,21937412,25091.125,36462.4062,38040.6289,37406.9805,46805.7891,42903.9414,33362.8633,54484.8008,36414.4258,40665.082 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.40691.40691.2","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,2,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,23614896,19902.084,25722.5449,30856.2891,53319.3359,17193.6094,88146.3125,82855.4922,42723.2109,44937.7969,34712.3594 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.41760.41760.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,3,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,42251600,29582.5547,17857.0117,32220.4473,46160.5039,69615.25,24384.7812,24639.2344,61988.4805,28249.7246,39099.5781 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.41769.41769.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",0.9925,3,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,54659052,35201.3281,20490.1738,36982.5273,60244.6719,86075.9141,35940.3945,31682.4629,81067.7969,36042.9336,55780.2695 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.42141.42141.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VTEQLIEAINNGDFEAYTK","n[230]VTEQLIEAINNGDFEAYTK",1,3,353,371,"CAMK2D","","sp|Q13557|KCC2D_HUMAN","Q13557","","Calcium/calmodulin-dependent protein kinase type II subunit delta",TRUE,1,38082916,29490.8418,42304.6992,64342.2188,53508.7109,59340.5703,120144.7266,46964.8555,75260.3672,64764.7734,55852.5195 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.43194.43194.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VVPVSLSEVYLLQCNMK","n[230]VVPVSLSEVYLLQCNMK",1,3,678,694,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,0.55,18145966,64383.0625,72356.75,62743.9414,83371.1094,160412.4219,65540.2969,115095.0391,73954.4844,64807.9141,74519.0156 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.43245.43245.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","VVPVSLSEVYLLQCNMK","n[230]VVPVSLSEVYLLQCNMK",1,3,678,694,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,1,26033156,46445.7109,46907.8828,48813.9492,56522.8516,92719.6953,65682.0469,81809.6328,58241.6367,50470.1406,60289.3867 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.43806.43806.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","MSNWQGAIDSCLEALELDPSNTK","n[230]MSNWQGAIDSCLEALELDPSNTK",1,3,286,308,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,0.69,52481592,148117.8594,92800.6094,221245.25,120612.1875,274593.2812,355536.0938,204307.1875,280591.625,264797.7188,157907.4219 +"16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.43952.43952.3","16CPTAC_CCRCC_W_JHU_20180322_LUMOS_f01.mzML","PTLWALLNSEYVTEEK","n[230]PTLWALLNSEYVTEEK",1,3,2120,2135,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,0,79958.6016,78765.4922,58813.5,70517.5703,50280.9492,55388.6875,106719.5078,66978.3203,77686.1406,89003.4688 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.04217.04217.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","MDDSDQDSCR","M[147]DDS[316]DQDSCR",0.9649,2,198,207,"PAX8","","sp|Q06710|PAX8_HUMAN","Q06710","","Paired box protein",TRUE,1,0,39884.5547,24974.3711,10091.1748,45095.1836,65185.8672,11669.0918,46138.5039,12993.4316,7988.5972,28517.9414 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.04442.04442.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","SSDGGSEEPPDRR","n[230]SSDGGSEEPPDRR",1,3,21,33,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,0.46,29357696,80028.9844,87967.7031,101598.375,100496.8203,161275.25,75225.3281,102696.9766,151036.8125,112668.5312,87605.2266 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.06260.06260.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","MDDSDQDSCR","n[230]MDDSDQDSCR",1,2,198,207,"PAX8","","sp|Q06710|PAX8_HUMAN","Q06710","","Paired box protein",TRUE,1,0,645713.125,424796.3125,158219.7656,768707.3125,1102303.375,143281.8125,740439.8125,208636,127572.9922,468972.4688 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.07347.07347.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","AEAEAEAGSPRPDPR","n[230]AEAEAEAGSPRPDPR",1,3,4637,4651,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0,16365115,56689.6445,23033.5801,53335.7188,58941.5312,33175.4492,161275.4531,35977.3672,39647.7148,16958.6289,59307.1016 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.08148.08148.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","QDGDYSPDNSAQPGDR","n[230]QDGDYSPDNSAQPGDR",1,2,309,324,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,0,607792704,311020.75,83619.4922,15097.6104,244208.8125,32794.9023,23036.8516,147349.2031,34465.832,34978.2461,103739.0312 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.08283.08283.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","QDGDYSPDNSAQPGDR","n[230]QDGDYSPDNSAQPGDR",1,3,309,324,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,1,44890952,73168.4844,48403.0742,44231.7891,74292.75,92910.3984,37685.4336,54651.9258,40100.1172,31234.9414,47870.6953 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.08693.08693.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","QAIVNASR","n[230]QAIVNASR",0.9765,2,439,446,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,1,38503400,264351.5312,73569.4766,104912.6797,925377.4375,926166.5625,115570.0391,255436.5469,359862.0625,118511.7656,222946.0781 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.11554.11554.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","EGQGEGETQEAAAATAAAR","n[230]EGQGEGETQEAAAATAAAR",1,2,3681,3699,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,78320048,286248.1875,5069.1895,148892.875,174360.5625,23365.2344,1148353,0,90918.5547,11632.6582,230870.7344 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.14929.14929.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","ESTESSNTTIEDEDVK","n[230]ESTESSNTTIEDEDVK",1,2,329,344,"CAMK2D","","sp|Q13557|KCC2D_HUMAN","Q13557","","Calcium/calmodulin-dependent protein kinase type II subunit delta",TRUE,0.53,323311072,170361.1406,110277.1016,138648.9688,223351.3125,956790.5625,148163.6094,261563.7812,157353.5938,63688.7539,157772.6719 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.14932.14932.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","ESTESSNTTIEDEDVK","n[230]ESTESSNTTIEDEDVK",1,2,329,344,"CAMK2D","","sp|Q13557|KCC2D_HUMAN","Q13557","","Calcium/calmodulin-dependent protein kinase type II subunit delta",TRUE,0.84,367648320,294106.0938,197443.0938,211006.4219,347610.2188,1605381.625,210632.7656,287321.125,235184.5312,65819.9688,214612.3438 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.14999.14999.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","LTMLNTVSK","n[230]LTM[147]LNTVSK",0.9685,3,68,76,"SH3GL1","","sp|Q99961|SH3G1_HUMAN","Q99961","","Endophilin-A2",TRUE,1,102373936,251949.125,222550.4375,368102.75,308361.75,211980.5,354011.0312,235623,314508.6562,529611.75,287265.7812 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.15353.15353.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","YQQETSVSQLPGRPK","n[230]YQQETSVSQLPGRPK",1,3,1564,1578,"TANC2","","sp|Q9HCD6|TANC2_HUMAN","Q9HCD6","","Protein TANC2",TRUE,0.51,34279500,170198.5781,181599.8125,231989.8438,181305.1562,202064.2188,182056.5,217149.4531,250748.7031,417306.125,197622.9688 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.15360.15360.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","QETVDCLKK","n[230]QETVDCLKK",0.9997,3,285,293,"CAMK2D","CAMK2A","sp|Q13557|KCC2D_HUMAN","Q13557","sp|Q9UQM7|KCC2A_HUMAN","Calcium/calmodulin-dependent protein kinase type II subunit delta",FALSE,1,28139004,582990.0625,460514.4062,417378.2188,784666.8125,2302350,582810.6875,761050.875,905113.0625,408943.625,720424.8125 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.15775.15775.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","GAILTTMLATR","n[230]GAILTTM[147]LATR",0.9993,3,302,312,"CAMK2D","CAMK2A;CAMK2B","sp|Q13557|KCC2D_HUMAN","Q13557","sp|Q13554|KCC2B_HUMAN;sp|Q9UQM7|KCC2A_HUMAN","Calcium/calmodulin-dependent protein kinase type II subunit delta",FALSE,1,41957356,233198.9375,647530.5,291124.5938,207511.2656,183859.0625,236534.7031,259046.6719,266516,505518.5,317696.9375 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.18335.18335.4","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","KGGDGIKPPPIIGR","n[230]KGGDGIKPPPIIGR",1,4,5,18,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0.53,852943488,626924.1875,493673.1875,549643.9375,669143.25,557778.375,600955.625,620787.0625,692777.875,751812.25,614106.75 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.19909.19909.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","SSLYCSDIGK","n[230]SSLYCSDIGK",1,2,379,388,"DHTKD1","","sp|Q96HY7|DHTK1_HUMAN","Q96HY7","","2-oxoadipate dehydrogenase complex component",TRUE,0.78,574903552,1490700.375,777483.9375,274506.375,1270474.25,195244.4375,193378.8281,707655.9375,217172.8438,576605.5,493141.75 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.20818.20818.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","GCGVVEFK","n[230]GCGVVEFK",0.9993,2,142,149,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,84356144,655077.0625,691005.75,413556.125,820350.0625,1725507.25,477492.875,711612.375,480527,527165.3125,627089.5625 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.21141.21141.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","EVTLGQVAK","n[230]EVTLGQVAK",1,2,858,866,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,134854928,563873,634774.4375,276654.25,426296.1875,295429.5,1566543.25,598150.625,584907,2069509.125,634058.0625 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.22375.22375.4","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","TDAFSQHHLEPLECPFER","n[230]TDAFS[316]QHHLEPLECPFER",1,4,225,242,"PAX8","","sp|Q06710|PAX8_HUMAN","Q06710","","Paired box protein",TRUE,0.7,58449232,458507.2188,513900.5625,226675.6719,617443.75,602702.8125,242153.3906,593551.625,234262.2812,333595.3438,393703.7188 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.22693.22693.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","YLEANMTQSALPK","n[230]YLEANM[147]TQSALPK",1,2,282,294,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0,57207080,230010.5625,171998.4219,289487.75,284056.0625,279422.75,324813.2812,215798.75,300698.5625,268676.5,265244.1562 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.23568.23568.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","GFIMAEVMK","n[230]GFIMAEVM[147]K",0.9998,3,341,349,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0.53,192811952,381783.25,320458.0312,293958.4062,455412.3125,314296.4062,320917,354925.3125,412719.375,285399.3438,322876.8125 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.27297.27297.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NIGNTFFK","n[230]NIGNTFFK",0.9999,2,228,235,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,1,308300352,1407065.5,1176072.875,1140584.875,2051653.875,2011354,953537.5625,1140141.125,1015642.375,1213439.75,1162606.25 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.27978.27978.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","MSIYQAMWK","n[230]MSIYQAM[147]WK",0.9987,2,2243,2251,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,49858092,195778.5156,156972.75,150975.2031,144945.9688,202314.625,569375.5,210106.9844,200318.7031,620879.625,221239.9688 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.30118.30118.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","LYGPTNFSPIINHVAR","n[230]LYGPTNFSPIINHVAR",1,3,391,406,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,1,818442432,444449.6562,333486.5312,336277.8125,474924.5312,583425.25,455661.5,461092.3438,509625.7188,212036.7344,393608.9062 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.33926.33926.4","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","DETSGLHLLPLPESAPALPTEEQVQR","n[230]DETS[316]GLHLLPLPESAPALPTEEQVQR",1,4,1105,1130,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,27931840,93912.0859,73017.7969,105501.5078,81444.6328,106202.4375,136859.3594,101720.3828,85035.3359,173821.5,95881.3125 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.36993.36993.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","VFISNIPYDMK","n[230]VFISNIPYDMK",1,2,102,112,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,0,213793568,274607.6562,287806.4375,142782.8906,336661.3125,613073.3125,221936.8125,309082.8125,214189.9688,216644.1094,213545.7344 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.37251.37251.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","VFFDVDIGGER","n[230]VFFDVDIGGER",1,2,18,28,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,1,135256704,423658.875,368475,375158.625,595656.125,504886.0625,410409.9062,421033.1562,481889.0938,458576.1562,390816.9375 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.37258.37258.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","VFFDVDIGGER","n[230]VFFDVDIGGER",1,2,18,28,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,0.7,119022536,247996.5781,198754.5781,182371.2031,342746.625,242807.2969,201411.5938,242962.125,177235.2969,172215.6094,215763.6875 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.37385.37385.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","VFFDVDIGGER","n[230]VFFDVDIGGER",1,2,18,28,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,0.83,34606448,269148.1875,264996.5625,207258.7031,387409.9062,385264.2812,278787.25,352958.0938,326427.5625,245497.6875,322449 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.39432.39432.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NLPFDLTWQK","n[230]NLPFDLTWQK",1,2,529,538,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,219495120,905735.75,884228.8125,541994.5,1104416.625,2232653.5,769780.6875,1162127.625,560233.5,656731.5625,747008.125 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.40586.40586.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,577487424,455174.9375,374895.125,369373.9062,532853.6875,377832.5,417925.25,447886.0938,569163.5,365027.2188,428961.0625 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.41044.41044.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0,32589512,131456.6406,115541.7266,104787.4688,158574.4375,145473.2344,120317.9141,119284.8203,155569.7656,108984.6016,135410.625 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.41389.41389.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,23473386,146337.2031,112537.0469,121689.4531,165904.375,150646.5938,158694.375,136980.1562,189462.1875,136669.3281,147227.0938 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.41415.41415.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,1,28783936,143430.1406,115676.2188,113914.6953,163258.2344,145756.3906,129612.1094,129360,157746.9688,128474.9922,135603.2188 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.41964.41964.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","NYIVEDGDIIFFK","n[230]NYIVEDGDIIFFK",1,2,374,386,"OLA1","","sp|Q9NTK5|OLA1_HUMAN","Q9NTK5","","Obg-like ATPase 1",TRUE,0,11347740,106565.4531,107700.4766,107787.6406,118916.9922,107449.9062,101757.6875,105692.7812,122248.8281,179382.0938,105824.6094 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.42210.42210.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","TIELSDDDFLGECECTLGQIVSSK","n[230]TIELS[316]DDDFLGECECTLGQIVSSK",1,3,86,109,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,0.58,0,48777.8867,42912.3398,37636.5039,54476.2656,75080.4141,27422.7656,56114.1719,65788.3359,29758.7129,48177.3555 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.42698.42698.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","AVPVWDVLASGYVSR","n[230]AVPVWDVLASGYVSR",1,2,2533,2547,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0.83,174371808,322448.8438,146438.1406,225681.625,305485.7812,213480.8438,980352.3125,224591.4375,249991.2344,548354.9375,340692.2188 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43223.43223.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","TIELSDDDFLGECECTLGQIVSSK","n[230]TIELSDDDFLGECECTLGQIVS[316]SK",1,3,86,109,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,0,0,47441.75,42593.125,34984.9922,51164.2109,71581.8828,27126.6055,49920.3672,61010.0586,26807.5566,50033.0078 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43482.43482.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","SDPLCVLFLNTSGQQWYEVER","n[230]SDPLCVLFLNTS[316]GQQWYEVER",1,3,27,47,"CPNE3","","sp|O75131|CPNE3_HUMAN","O75131","","Copine-3",TRUE,0.84,18769052,176958.6719,137091.8594,106044.6016,222733.8281,251033.0938,72343.1094,174954.9219,169680.6719,74412.8047,128556.2578 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43554.43554.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,3,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,43202416,41619.168,49190.7617,37504.8555,44412.4688,65305.5781,47820.7305,54133.8164,37978.6992,84100.1094,48975.4883 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43562.43562.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,2,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,1,40426140,87986.5312,117469.6172,53320.3477,111176.1875,246044.4219,67546.0859,131629.4844,70657.6875,77868.3594,86337.0859 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43605.43605.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","IGGGIGFGGLEAMNSMGGFGGVGR","n[230]IGGGIGFGGLEAMNSMGGFGGVGR",1,3,377,400,"MYEF2","","sp|Q9P2K5|MYEF2_HUMAN","Q9P2K5","","Myelin expression factor 2",TRUE,0,0,31483.1602,46732.5,34811.7773,31429.8223,38235.8359,41466.0352,37983.0781,32965.4727,50718.332,32575.7988 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43698.43698.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","AVPVWDVLASGYVSGAAR","n[230]AVPVWDVLASGYVSGAAR",1,3,4670,4687,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0,24352304,18913.9551,18430.5742,23662.7012,23380.3691,31197.4531,22906.9043,25586.7188,22859.916,24170.2852,23688.5195 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43711.43711.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","AVPVWDVLASGYVSGAAR","n[230]AVPVWDVLASGYVSGAAR",1,3,4670,4687,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,0,0,20426,20898.4668,18721.1504,22153.2617,30320.668,20762.3145,22914.25,20001.4941,25546.123,20352.9941 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43717.43717.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","AVPVWDVLASGYVSGAAR","n[230]AVPVWDVLASGYVSGAAR",1,3,4670,4687,"EPPK1","","sp|P58107|EPIPL_HUMAN","P58107","","Epiplakin",TRUE,1,30402308,17394.6738,16882.2852,18113.1719,20978.8965,32042.8125,20866.4355,26597.0215,21222.6465,24294.4336,15848.207 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.43912.43912.3","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","MSNWQGAIDSCLEALELDPSNTK","M[147]S[316]NWQGAIDSCLEALELDPSNTK",1,3,286,308,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,1,27560010,122582.1953,82481.7656,79387.1484,133003.0625,178821.0625,89622.9766,136408.0781,120745.6406,73213.2656,114462.5547 +"17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.46161.46161.2","17CPTAC_CCRCC_W_JHU_20180517_LUMOS_f01.mzML","MSNWQGAIDSCLEALELDPSNTK","n[230]MSNWQGAIDSCLEALELDPSNTK",1,2,286,308,"PPID","","sp|Q08752|PPID_HUMAN","Q08752","","Peptidyl-prolyl cis-trans isomerase D",TRUE,0,0,24850.3398,22807.7891,14892.9639,26095.6797,36738.7422,12269.0049,26776.502,20596.3926,14881.5625,19730.4785 diff --git a/inst/tinytest/raw_data/SpectroMine/spectromine_annotation.csv b/inst/tinytest/raw_data/SpectroMine/spectromine_annotation.csv new file mode 100644 index 000000000..e25d86293 --- /dev/null +++ b/inst/tinytest/raw_data/SpectroMine/spectromine_annotation.csv @@ -0,0 +1,73 @@ +"Run","TechRepMixture","Fraction","Channel","Condition","Mixture","BioReplicate" +"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_1.raw","1","1","TMT6_126",3,"1",1 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+"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_8.raw","1","8","TMT6_131",1,"1",3 +"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_9.raw","1","9","TMT6_131",1,"1",3 +"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_10.raw","1","10","TMT6_131",1,"1",3 +"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_11.raw","1","11","TMT6_131",1,"1",3 +"ch_19Jan2017_SM-1-1_Sp-6-2_CID-OT-MS3-Short_HpH_12.raw","1","12","TMT6_131",1,"1",3 diff --git a/inst/tinytest/test_converters_tmt.R b/inst/tinytest/test_converters_tmt.R new file mode 100644 index 000000000..5479961b2 --- /dev/null +++ b/inst/tinytest/test_converters_tmt.R @@ -0,0 +1,43 @@ +# TODO: change these tests + +context("PDtoMSstatsTMTFormat") +context("MaxQtoMSstatsTMTFormat") +context("SpectroMinetoMSstatsTMTFormat") + +test_that("PDtoMSstatsTMTFormat works", { + + expect_error(PDtoMSstatsTMTFormat(input = MSstatsTMT::raw.pd[, !colnames(MSstatsTMT::raw.pd) == "Protein.Accessions"], # missing columns in input + annotation = MSstatsTMT::annotation.pd)) + + expect_error(PDtoMSstatsTMTFormat(input = MSstatsTMT::raw.pd, + annotation = MSstatsTMT::annotation.pd[, !colnames(MSstatsTMT::annotation.pd) == "Condition"])) # missing columns in annotation + +}) + +test_that("MaxQtoMSstatsTMTFormat works", { + + expect_error(MaxQtoMSstatsTMTFormat(evidence = MSstatsTMT::evidence, proteinGroups = MSstatsTMT::proteinGroups, + annotation = MSstatsTMT::annotation.pd)) # wrong annotation file + +}) + +test_that("SpectroMinetoMSstatsTMTFormat works", { + + expect_error(SpectroMinetoMSstatsTMTFormat(input = MSstatsTMT::raw.mine, + annotation = MSstatsTMT::annotation.mine, + summaryforMultipleRows = average)) # wrong argument value + +}) + +test_that("PhilosophertoMSstatsTMTFormat works", { + + input_file_path = system.file("raw_data/Philosopher/msstats.csv", + package = "MSstatsTMT") + annotation_file_path = system.file("raw_data/Philosopher/MSstatsTMT_annotation.csv", + package = "MSstatsTMT") + input = data.table::fread(input_file_path) + annotation = data.table::fread(annotation_file_path) + msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) + expect_equal(nrow(msstats_format), 550) + +}) \ No newline at end of file From ea9337fc90ada4ff89f911e30330c917b23adb05 Mon Sep 17 00:00:00 2001 From: tonywu1999 Date: Thu, 9 Apr 2026 17:21:10 -0400 Subject: [PATCH 2/5] update manuals --- DESCRIPTION | 5 ++ NAMESPACE | 5 ++ man/MaxQtoMSstatsTMTFormat.Rd | 76 ++++++++++++++++++++++++ man/OpenMStoMSstatsTMTFormat.Rd | 60 +++++++++++++++++++ man/PDtoMSstatsTMTFormat.Rd | 74 +++++++++++++++++++++++ man/PhilosophertoMSstatsTMTFormat.Rd | 87 ++++++++++++++++++++++++++++ man/SpectroMinetoMSstatsTMTFormat.Rd | 73 +++++++++++++++++++++++ man/dot-getPhilosopherInput.Rd | 15 +++++ 8 files changed, 395 insertions(+) create mode 100644 man/MaxQtoMSstatsTMTFormat.Rd create mode 100644 man/OpenMStoMSstatsTMTFormat.Rd create mode 100644 man/PDtoMSstatsTMTFormat.Rd create mode 100644 man/PhilosophertoMSstatsTMTFormat.Rd create mode 100644 man/SpectroMinetoMSstatsTMTFormat.Rd create mode 100644 man/dot-getPhilosopherInput.Rd diff --git a/DESCRIPTION b/DESCRIPTION index cf29a4575..8edfce590 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -54,13 +54,18 @@ Collate: 'converters_DIAUmpiretoMSstatsFormat.R' 'converters_FragPipetoMSstatsFormat.R' 'converters_MaxQtoMSstatsFormat.R' + 'converters_MaxQtoMSstatsTMTFormat.R' 'converters_MetamorpheusToMSstatsFormat.R' 'converters_OpenMStoMSstatsFormat.R' + 'converters_OpenMStoMSstatsTMTFormat.R' 'converters_OpenSWATHtoMSstatsFormat.R' 'converters_PDtoMSstatsFormat.R' + 'converters_PDtoMSstatsTMTFormat.R' + 'converters_PhilosophertoMSstatsTMTFormat.R' 'converters_ProgenesistoMSstatsFormat.R' 'converters_ProteinProspectortoMSstatsTMTFormat.R' 'converters_SkylinetoMSstatsFormat.R' + 'converters_SpectroMinetoMSstatsTMTFormat.R' 'converters_SpectronauttoMSstatsFormat.R' 'utils_MSstatsConvert.R' 'utils_annotation.R' diff --git a/NAMESPACE b/NAMESPACE index 3865ee6be..cc2cfa210 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -15,13 +15,18 @@ export(MSstatsMakeAnnotation) export(MSstatsPreprocess) export(MSstatsSaveSessionInfo) export(MaxQtoMSstatsFormat) +export(MaxQtoMSstatsTMTFormat) export(MetamorpheusToMSstatsFormat) export(OpenMStoMSstatsFormat) +export(OpenMStoMSstatsTMTFormat) export(OpenSWATHtoMSstatsFormat) export(PDtoMSstatsFormat) +export(PDtoMSstatsTMTFormat) +export(PhilosophertoMSstatsTMTFormat) export(ProgenesistoMSstatsFormat) export(ProteinProspectortoMSstatsTMTFormat) export(SkylinetoMSstatsFormat) +export(SpectroMinetoMSstatsTMTFormat) export(SpectronauttoMSstatsFormat) export(getDataType) export(getInputFile) diff --git a/man/MaxQtoMSstatsTMTFormat.Rd b/man/MaxQtoMSstatsTMTFormat.Rd new file mode 100644 index 000000000..cb6eae723 --- /dev/null +++ b/man/MaxQtoMSstatsTMTFormat.Rd @@ -0,0 +1,76 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_MaxQtoMSstatsTMTFormat.R +\name{MaxQtoMSstatsTMTFormat} +\alias{MaxQtoMSstatsTMTFormat} +\title{Generate MSstatsTMT required input format from MaxQuant output} +\usage{ +MaxQtoMSstatsTMTFormat( + evidence, + proteinGroups, + annotation, + which.proteinid = "Proteins", + rmProt_Only.identified.by.site = FALSE, + useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, + append = FALSE, + verbose = TRUE, + log_file_path = NULL, + ... +) +} +\arguments{ +\item{evidence}{name of 'evidence.txt' data, which includes feature-level data.} + +\item{proteinGroups}{name of 'proteinGroups.txt' data.} + +\item{annotation}{data frame which contains column Run, Fraction, TechRepMixture, Mixture, Channel, BioReplicate, Condition. Refer to the example 'annotation.mq' for the meaning of each column.} + +\item{which.proteinid}{Use 'Proteins' (default) column for protein name. 'Leading.proteins' or 'Leading.razor.proteins' or 'Gene.names' can be used instead to get the protein ID with single protein. However, those can potentially have the shared peptides.} + +\item{rmProt_Only.identified.by.site}{TRUE will remove proteins with '+' in 'Only.identified.by.site' column from proteinGroups.txt, which was identified only by a modification site. FALSE is the default.} + +\item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. +We assume to use unique peptide for each protein.} + +\item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} + +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} + +\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} + +\item{use_log_file}{logical. If TRUE, information about data processing +will be saved to a file.} + +\item{append}{logical. If TRUE, information about data processing will be added +to an existing log file.} + +\item{verbose}{logical. If TRUE, information about data processing wil be printed +to the console.} + +\item{log_file_path}{character. Path to a file to which information about +data processing will be saved. +If not provided, such a file will be created automatically. +If \code{append = TRUE}, has to be a valid path to a file.} + +\item{...}{additional parameters to \code{data.table::fread}.} +} +\value{ +data.frame of class "MSstatsTMT" +} +\description{ +Generate MSstatsTMT required input format from MaxQuant output +} +\examples{ +evidence = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_ev.csv", + package = "MSstatsConvert")) +proteinGroups = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_pg.csv", + package = "MSstatsConvert")) +annotation.mq = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_annotation.csv", + package = "MSstatsConvert")) +input.mq <- MaxQtoMSstatsTMTFormat(evidence, proteinGroups, annotation.mq) +head(input.mq) + +} diff --git a/man/OpenMStoMSstatsTMTFormat.Rd b/man/OpenMStoMSstatsTMTFormat.Rd new file mode 100644 index 000000000..4b2c94349 --- /dev/null +++ b/man/OpenMStoMSstatsTMTFormat.Rd @@ -0,0 +1,60 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_OpenMStoMSstatsTMTFormat.R +\name{OpenMStoMSstatsTMTFormat} +\alias{OpenMStoMSstatsTMTFormat} +\title{Generate MSstatsTMT required input format for OpenMS output} +\usage{ +OpenMStoMSstatsTMTFormat( + input, + useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, + summaryforMultiplePSMs = sum, + use_log_file = TRUE, + append = FALSE, + verbose = TRUE, + log_file_path = NULL, + ... +) +} +\arguments{ +\item{input}{MSstatsTMT report from OpenMS} + +\item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. +We assume to use unique peptide for each protein.} + +\item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} + +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} + +\item{summaryforMultiplePSMs}{sum(default) or max - when there are multiple measurements for certain feature in certain run, select the feature with the largest summation or maximal value.} + +\item{use_log_file}{logical. If TRUE, information about data processing +will be saved to a file.} + +\item{append}{logical. If TRUE, information about data processing will be added +to an existing log file.} + +\item{verbose}{logical. If TRUE, information about data processing wil be printed +to the console.} + +\item{log_file_path}{character. Path to a file to which information about +data processing will be saved. +If not provided, such a file will be created automatically. +If \code{append = TRUE}, has to be a valid path to a file.} + +\item{...}{additional parameters to \code{data.table::fread}.} +} +\value{ +\code{data.frame} of class \code{MSstatsTMT}. +} +\description{ +Generate MSstatsTMT required input format for OpenMS output +} +\examples{ +raw.om = data.table::fread(system.file("tinytest/raw_data/OpenMSTMT/openmstmt_input.csv", + package = "MSstatsConvert")) +input.om <- OpenMStoMSstatsTMTFormat(raw.om) +head(input.om) + +} diff --git a/man/PDtoMSstatsTMTFormat.Rd b/man/PDtoMSstatsTMTFormat.Rd new file mode 100644 index 000000000..f99360b66 --- /dev/null +++ b/man/PDtoMSstatsTMTFormat.Rd @@ -0,0 +1,74 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_PDtoMSstatsTMTFormat.R +\name{PDtoMSstatsTMTFormat} +\alias{PDtoMSstatsTMTFormat} +\title{Convert Proteome Discoverer output to MSstatsTMT format.} +\usage{ +PDtoMSstatsTMTFormat( + input, + annotation, + which.proteinid = "Protein.Accessions", + useNumProteinsColumn = TRUE, + useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, + append = FALSE, + verbose = TRUE, + log_file_path = NULL, + ... +) +} +\arguments{ +\item{input}{PD report or a path to it.} + +\item{annotation}{annotation with Run, Fraction, TechRepMixture, Mixture, Channel, +BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column.} + +\item{which.proteinid}{Use 'Protein.Accessions'(default) column for protein name. 'Master.Protein.Accessions' can be used instead to get the protein name with single protein.} + +\item{useNumProteinsColumn}{logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet.} + +\item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. +We assume to use unique peptide for each protein.} + +\item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} + +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} + +\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} + +\item{use_log_file}{logical. If TRUE, information about data processing +will be saved to a file.} + +\item{append}{logical. If TRUE, information about data processing will be added +to an existing log file.} + +\item{verbose}{logical. If TRUE, information about data processing wil be printed +to the console.} + +\item{log_file_path}{character. Path to a file to which information about +data processing will be saved. +If not provided, such a file will be created automatically. +If \code{append = TRUE}, has to be a valid path to a file.} + +\item{...}{additional parameters to \code{data.table::fread}.} +} +\value{ +\code{data.frame} of class \code{MSstatsTMT} +} +\description{ +Convert Proteome Discoverer output to MSstatsTMT format. +} +\examples{ +raw.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pdtmt_input.csv", + package = "MSstatsConvert")) +annotation.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annotation.csv", + package = "MSstatsConvert")) +head(raw.pd) +head(annotation.pd) +input.pd <- PDtoMSstatsTMTFormat(raw.pd, annotation.pd) +head(input.pd) + +} diff --git a/man/PhilosophertoMSstatsTMTFormat.Rd b/man/PhilosophertoMSstatsTMTFormat.Rd new file mode 100644 index 000000000..ee2cc5e79 --- /dev/null +++ b/man/PhilosophertoMSstatsTMTFormat.Rd @@ -0,0 +1,87 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_PhilosophertoMSstatsTMTFormat.R +\name{PhilosophertoMSstatsTMTFormat} +\alias{PhilosophertoMSstatsTMTFormat} +\title{Convert Philosopher (Fragpipe) output to MSstatsTMT format.} +\usage{ +PhilosophertoMSstatsTMTFormat( + input, + annotation, + protein_id_col = "Protein", + peptide_id_col = "Peptide.Sequence", + Purity_cutoff = 0.6, + PeptideProphet_prob_cutoff = 0.7, + useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, + rmPeptide_OxidationM = TRUE, + rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, + append = FALSE, + verbose = TRUE, + log_file_path = NULL, + ... +) +} +\arguments{ +\item{input}{data.frame of \code{msstats.csv} file produced by Philosopher} + +\item{annotation}{annotation with Run, Fraction, TechRepMixture, Mixture, Channel, +BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column. Channel column should be +consistent with the channel columns (Ignore the prefix "Channel ") in msstats.csv file. Run column should be consistent with the Spectrum.File columns in msstats.csv file.} + +\item{protein_id_col}{Use 'Protein'(default) column for protein name. +'Master.Protein.Accessions' can be used instead to get the protein ID with single protein.} + +\item{peptide_id_col}{Use 'Peptide.Sequence'(default) column for peptide sequence. +'Modified.Peptide.Sequence' can be used instead to get the modified peptide sequence.} + +\item{Purity_cutoff}{Cutoff for purity. Default is 0.6} + +\item{PeptideProphet_prob_cutoff}{Cutoff for the peptide identification probability. Default is 0.7. +The probability is confidence score determined by PeptideProphet and higher values indicate greater confidence.} + +\item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. +We assume to use unique peptide for each protein.} + +\item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} + +\item{rmPeptide_OxidationM}{TRUE (default) will remove the peptides including oxidation (M) sequence.} + +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} + +\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} + +\item{use_log_file}{logical. If TRUE, information about data processing +will be saved to a file.} + +\item{append}{logical. If TRUE, information about data processing will be added +to an existing log file.} + +\item{verbose}{logical. If TRUE, information about data processing wil be printed +to the console.} + +\item{log_file_path}{character. Path to a file to which information about +data processing will be saved. +If not provided, such a file will be created automatically. +If \code{append = TRUE}, has to be a valid path to a file.} + +\item{...}{additional parameters to \code{data.table::fread}.} +} +\value{ +\code{data.frame} of class \code{MSstatsTMT} +} +\description{ +Convert Philosopher (Fragpipe) output to MSstatsTMT format. +} +\examples{ +input_file_path = system.file("tinytest/raw_data/Philosopher/msstats.csv", + package = "MSstatsTMT") +annotation_file_path = system.file("tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv", + package = "MSstatsTMT") +input = data.table::fread(input_file_path) +annotation = data.table::fread(annotation_file_path) +msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) +head(msstats_format) + +} diff --git a/man/SpectroMinetoMSstatsTMTFormat.Rd b/man/SpectroMinetoMSstatsTMTFormat.Rd new file mode 100644 index 000000000..3a179444b --- /dev/null +++ b/man/SpectroMinetoMSstatsTMTFormat.Rd @@ -0,0 +1,73 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_SpectroMinetoMSstatsTMTFormat.R +\name{SpectroMinetoMSstatsTMTFormat} +\alias{SpectroMinetoMSstatsTMTFormat} +\title{Import data from SpectroMine} +\usage{ +SpectroMinetoMSstatsTMTFormat( + input, + annotation, + filter_with_Qvalue = TRUE, + qvalue_cutoff = 0.01, + useUniquePeptide = TRUE, + rmPSM_withfewMea_withinRun = TRUE, + rmProtein_with1Feature = FALSE, + summaryforMultipleRows = sum, + use_log_file = TRUE, + append = FALSE, + verbose = TRUE, + log_file_path = NULL, + ... +) +} +\arguments{ +\item{input}{data name of SpectroMine PSM output. Read PSM sheet.} + +\item{annotation}{data frame which contains column Run, Fraction, TechRepMixture, Mixture, Channel, BioReplicate, Condition. Refer to the example 'annotation.mine' for the meaning of each column.} + +\item{filter_with_Qvalue}{TRUE(default) will filter out the intensities that have greater than qvalue_cutoff in EG.Qvalue column. Those intensities will be replaced with NA and will be considered as censored missing values for imputation purpose.} + +\item{qvalue_cutoff}{Cutoff for EG.Qvalue. default is 0.01.} + +\item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. +We assume to use unique peptide for each protein.} + +\item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} + +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} + +\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} + +\item{use_log_file}{logical. If TRUE, information about data processing +will be saved to a file.} + +\item{append}{logical. If TRUE, information about data processing will be added +to an existing log file.} + +\item{verbose}{logical. If TRUE, information about data processing wil be printed +to the console.} + +\item{log_file_path}{character. Path to a file to which information about +data processing will be saved. +If not provided, such a file will be created automatically. +If \code{append = TRUE}, has to be a valid path to a file.} + +\item{...}{additional parameters to \code{data.table::fread}.} +} +\value{ +\code{data.frame} of class \code{MSstatsTMT} +} +\description{ +Import data from SpectroMine +} +\examples{ +raw.mine = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_input.csv", + package = "MSstatsConvert")) +annotation.mine = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_annotation.csv", + package = "MSstatsConvert")) +head(raw.mine) +head(annotation.mine) +input.mine <- SpectroMinetoMSstatsTMTFormat(raw.mine, annotation.mine) +head(input.mine) + +} diff --git a/man/dot-getPhilosopherInput.Rd b/man/dot-getPhilosopherInput.Rd new file mode 100644 index 000000000..c851ee325 --- /dev/null +++ b/man/dot-getPhilosopherInput.Rd @@ -0,0 +1,15 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/converters_PhilosophertoMSstatsTMTFormat.R +\name{.getPhilosopherInput} +\alias{.getPhilosopherInput} +\title{Convert Philosopher parameters to consistent format} +\usage{ +.getPhilosopherInput(input, path, folder) +} +\arguments{ +\item{input}{data.frame of \code{msstats.csv} file produced by Philosopher} +} +\description{ +Convert Philosopher parameters to consistent format +} +\keyword{internal} From 9fc5b0ffa1587d2c208f3528be76837e5b62711b Mon Sep 17 00:00:00 2001 From: Tony Wu Date: Fri, 10 Apr 2026 09:02:12 -0400 Subject: [PATCH 3/5] add unit tests --- R/converters_PhilosophertoMSstatsTMTFormat.R | 4 +- .../test_converters_MaxQtoMSstatsTMTFormat.R | 33 ++++++++++++++ ...test_converters_OpenMStoMSstatsTMTFormat.R | 22 ++++++++++ .../test_converters_PDtoMSstatsTMTFormat.R | 36 ++++++++++++++++ ...converters_PhilosophertoMSstatsTMTFormat.R | 25 +++++++++++ ...ters_ProteinProspectortoMSstatsTMTFormat.R | 20 +++++---- ...converters_SpectroMinetoMSstatsTMTFormat.R | 31 +++++++++++++ inst/tinytest/test_converters_tmt.R | 43 ------------------- man/PhilosophertoMSstatsTMTFormat.Rd | 4 +- 9 files changed, 163 insertions(+), 55 deletions(-) create mode 100644 inst/tinytest/test_converters_MaxQtoMSstatsTMTFormat.R create mode 100644 inst/tinytest/test_converters_OpenMStoMSstatsTMTFormat.R create mode 100644 inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R create mode 100644 inst/tinytest/test_converters_PhilosophertoMSstatsTMTFormat.R create mode 100644 inst/tinytest/test_converters_SpectroMinetoMSstatsTMTFormat.R delete mode 100644 inst/tinytest/test_converters_tmt.R diff --git a/R/converters_PhilosophertoMSstatsTMTFormat.R b/R/converters_PhilosophertoMSstatsTMTFormat.R index 9e5158002..3bed3ad8a 100644 --- a/R/converters_PhilosophertoMSstatsTMTFormat.R +++ b/R/converters_PhilosophertoMSstatsTMTFormat.R @@ -21,9 +21,9 @@ #' #' @examples #' input_file_path = system.file("tinytest/raw_data/Philosopher/msstats.csv", -#' package = "MSstatsTMT") +#' package = "MSstatsConvert") #' annotation_file_path = system.file("tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv", -#' package = "MSstatsTMT") +#' package = "MSstatsConvert") #' input = data.table::fread(input_file_path) #' annotation = data.table::fread(annotation_file_path) #' msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) diff --git a/inst/tinytest/test_converters_MaxQtoMSstatsTMTFormat.R b/inst/tinytest/test_converters_MaxQtoMSstatsTMTFormat.R new file mode 100644 index 000000000..f123813ba --- /dev/null +++ b/inst/tinytest/test_converters_MaxQtoMSstatsTMTFormat.R @@ -0,0 +1,33 @@ +# Test MaxQtoMSstatsTMTFormat --------------------------- +mq_ev = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_ev.csv", + package = "MSstatsConvert")) +mq_pg = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_pg.csv", + package = "MSstatsConvert")) +annot = data.table::fread(system.file("tinytest/raw_data/MaxQuantTMT/mq_annotation.csv", + package = "MSstatsConvert")) +output = MaxQtoMSstatsTMTFormat(mq_ev, mq_pg, annot, use_log_file = FALSE) +expect_equal(ncol(output), 11) +expect_true(nrow(output) > 0) +expect_true("Run" %in% colnames(output)) +expect_true("ProteinName" %in% colnames(output)) +expect_true("PeptideSequence" %in% colnames(output)) +expect_true("Charge" %in% colnames(output)) +expect_true("Intensity" %in% colnames(output)) +expect_true("TechRepMixture" %in% colnames(output)) +expect_true("PSM" %in% colnames(output)) +expect_true("Mixture" %in% colnames(output)) +expect_true("Condition" %in% colnames(output)) +expect_true("BioReplicate" %in% colnames(output)) +expect_true("Channel" %in% colnames(output)) + +bad_annotation = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annotation.csv", + package = "MSstatsConvert")) + +expect_error(MaxQtoMSstatsTMTFormat(evidence = mq_ev, proteinGroups = mq_pg, + annotation = bad_annotation)) # wrong annotation file + +# Verify output intensities are present in input +intensity_cols = grep("Reporter.intensity.corrected", colnames(mq_ev), value = TRUE) +input_intensities = as.character(unlist(mq_ev[, intensity_cols, with = FALSE])) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) diff --git a/inst/tinytest/test_converters_OpenMStoMSstatsTMTFormat.R b/inst/tinytest/test_converters_OpenMStoMSstatsTMTFormat.R new file mode 100644 index 000000000..3f915dbe6 --- /dev/null +++ b/inst/tinytest/test_converters_OpenMStoMSstatsTMTFormat.R @@ -0,0 +1,22 @@ +# Test OpenMStoMSstatsTMTFormat --------------------------- +raw = data.table::fread(system.file("tinytest/raw_data/OpenMSTMT/openmstmt_input.csv", + package = "MSstatsConvert")) +output = OpenMStoMSstatsTMTFormat(raw, use_log_file = FALSE) +expect_equal(ncol(output), 11) +expect_true(nrow(output) > 0) +expect_true("Run" %in% colnames(output)) +expect_true("ProteinName" %in% colnames(output)) +expect_true("PeptideSequence" %in% colnames(output)) +expect_true("Charge" %in% colnames(output)) +expect_true("Intensity" %in% colnames(output)) +expect_true("TechRepMixture" %in% colnames(output)) +expect_true("PSM" %in% colnames(output)) +expect_true("Mixture" %in% colnames(output)) +expect_true("Condition" %in% colnames(output)) +expect_true("BioReplicate" %in% colnames(output)) +expect_true("Channel" %in% colnames(output)) + +# Verify output intensities are present in input +input_intensities = as.character(raw$Intensity) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) diff --git a/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R b/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R new file mode 100644 index 000000000..2adb23209 --- /dev/null +++ b/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R @@ -0,0 +1,36 @@ +# Test PDtoMSstatsTMTFormat --------------------------- +pd_raw = data.table::fread(system.file("tinytest/raw_data/PDTMT/pdtmt_input.csv", + package = "MSstatsConvert")) +annot = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annotation.csv", + package = "MSstatsConvert")) +output = PDtoMSstatsTMTFormat(pd_raw, annot, use_log_file = FALSE) +expect_equal(ncol(output), 11) +expect_true(nrow(output) > 0) +expect_true("Run" %in% colnames(output)) +expect_true("ProteinName" %in% colnames(output)) +expect_true("PeptideSequence" %in% colnames(output)) +expect_true("Charge" %in% colnames(output)) +expect_true("Intensity" %in% colnames(output)) +expect_true("TechRepMixture" %in% colnames(output)) +expect_true("PSM" %in% colnames(output)) +expect_true("Mixture" %in% colnames(output)) +expect_true("Condition" %in% colnames(output)) +expect_true("BioReplicate" %in% colnames(output)) +expect_true("Channel" %in% colnames(output)) + +raw.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pdtmt_input.csv", + package = "MSstatsConvert")) +annotation.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annotation.csv", + package = "MSstatsConvert")) + +expect_error(PDtoMSstatsTMTFormat(input = pd_raw[, !colnames(pd_raw) == "Protein.Accessions"], # missing columns in input + annotation = annot)) + +expect_error(PDtoMSstatsTMTFormat(input = pd_raw, + annotation = annot[, !colnames(annot) == "Condition"])) # missing columns in annotation + +# Verify output intensities are present in input +intensity_cols = grep("^Abundance", colnames(pd_raw), value = TRUE) +input_intensities = as.character(unlist(pd_raw[, intensity_cols, with = FALSE])) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) diff --git a/inst/tinytest/test_converters_PhilosophertoMSstatsTMTFormat.R b/inst/tinytest/test_converters_PhilosophertoMSstatsTMTFormat.R new file mode 100644 index 000000000..d79a6ac75 --- /dev/null +++ b/inst/tinytest/test_converters_PhilosophertoMSstatsTMTFormat.R @@ -0,0 +1,25 @@ +# Test PhilosophertoMSstatsTMTFormat --------------------------- +input = data.table::fread(system.file("tinytest/raw_data/Philosopher/msstats.csv", + package = "MSstatsConvert")) +annot = data.table::fread(system.file("tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv", + package = "MSstatsConvert")) +output = PhilosophertoMSstatsTMTFormat(input, annot, use_log_file = FALSE) +expect_equal(ncol(output), 11) +expect_equal(nrow(output), 550) +expect_true("Run" %in% colnames(output)) +expect_true("ProteinName" %in% colnames(output)) +expect_true("PeptideSequence" %in% colnames(output)) +expect_true("Charge" %in% colnames(output)) +expect_true("Intensity" %in% colnames(output)) +expect_true("TechRepMixture" %in% colnames(output)) +expect_true("PSM" %in% colnames(output)) +expect_true("Mixture" %in% colnames(output)) +expect_true("Condition" %in% colnames(output)) +expect_true("BioReplicate" %in% colnames(output)) +expect_true("Channel" %in% colnames(output)) + +# Verify output intensities are present in input +intensity_cols = grep("^Channel\\.", colnames(input), value = TRUE) +input_intensities = as.character(unlist(input[, intensity_cols, with = FALSE])) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) diff --git a/inst/tinytest/test_converters_ProteinProspectortoMSstatsTMTFormat.R b/inst/tinytest/test_converters_ProteinProspectortoMSstatsTMTFormat.R index 0d0823ff4..1c98d1509 100644 --- a/inst/tinytest/test_converters_ProteinProspectortoMSstatsTMTFormat.R +++ b/inst/tinytest/test_converters_ProteinProspectortoMSstatsTMTFormat.R @@ -1,11 +1,9 @@ # Test ProteinProspectortoMSstatsTMTFormat --------------------------- -input = system.file("tinytest/raw_data/ProteinProspector/Prospector_TotalTMT.txt", - package = "MSstatsConvert") -input = data.table::fread(input) -annot = system.file("tinytest/raw_data/ProteinProspector/Annotation.csv", - package = "MSstatsConvert") -annot = data.table::fread(annot) -output = ProteinProspectortoMSstatsTMTFormat(input, annot) +input = data.table::fread(system.file("tinytest/raw_data/ProteinProspector/Prospector_TotalTMT.txt", + package = "MSstatsConvert")) +annot = data.table::fread(system.file("tinytest/raw_data/ProteinProspector/Annotation.csv", + package = "MSstatsConvert")) +output = ProteinProspectortoMSstatsTMTFormat(input, annot, use_log_file = FALSE) expect_equal(ncol(output), 11) expect_equal(nrow(output), 528) expect_true("Run" %in% colnames(output)) @@ -24,4 +22,10 @@ expect_true("Channel" %in% colnames(output)) zero_value_entry = output[output$PeptideSequence == "DINKVAEDLESEGLMAEEVQAVQQQEVYGAMPR" & output$BioReplicate == "S1",]$Intensity -expect_true(is.na(zero_value_entry)) \ No newline at end of file +expect_true(is.na(zero_value_entry)) + +# Verify output intensities are present in input +intensity_cols = grep("^Int ", colnames(input), value = TRUE) +input_intensities = as.character(unlist(input[, intensity_cols, with = FALSE])) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) \ No newline at end of file diff --git a/inst/tinytest/test_converters_SpectroMinetoMSstatsTMTFormat.R b/inst/tinytest/test_converters_SpectroMinetoMSstatsTMTFormat.R new file mode 100644 index 000000000..a5be66ba0 --- /dev/null +++ b/inst/tinytest/test_converters_SpectroMinetoMSstatsTMTFormat.R @@ -0,0 +1,31 @@ +# Test SpectroMinetoMSstatsTMTFormat --------------------------- +raw = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_input.csv", + package = "MSstatsConvert")) +annot = data.table::fread(system.file("tinytest/raw_data/SpectroMine/spectromine_annotation.csv", + package = "MSstatsConvert")) +output = SpectroMinetoMSstatsTMTFormat(raw, annot, use_log_file = FALSE) +expect_equal(ncol(output), 11) +expect_true(nrow(output) > 0) +expect_true("Run" %in% colnames(output)) +expect_true("ProteinName" %in% colnames(output)) +expect_true("PeptideSequence" %in% colnames(output)) +expect_true("Charge" %in% colnames(output)) +expect_true("Intensity" %in% colnames(output)) +expect_true("TechRepMixture" %in% colnames(output)) +expect_true("PSM" %in% colnames(output)) +expect_true("Mixture" %in% colnames(output)) +expect_true("Condition" %in% colnames(output)) +expect_true("BioReplicate" %in% colnames(output)) +expect_true("Channel" %in% colnames(output)) + +expect_error(SpectroMinetoMSstatsTMTFormat(input = raw, + annotation = annot, + summaryforMultipleRows = average)) # wrong argument value + +# Verify output intensities are present in input +intensity_cols = grep("^PSM\\.TMT", colnames(raw), value = TRUE) +input_intensities = as.character(unlist(raw[, intensity_cols, with = FALSE])) +output_intensities = as.character(output$Intensity[!is.na(output$Intensity)]) +expect_true(all(output_intensities %in% input_intensities)) + + diff --git a/inst/tinytest/test_converters_tmt.R b/inst/tinytest/test_converters_tmt.R deleted file mode 100644 index 5479961b2..000000000 --- a/inst/tinytest/test_converters_tmt.R +++ /dev/null @@ -1,43 +0,0 @@ -# TODO: change these tests - -context("PDtoMSstatsTMTFormat") -context("MaxQtoMSstatsTMTFormat") -context("SpectroMinetoMSstatsTMTFormat") - -test_that("PDtoMSstatsTMTFormat works", { - - expect_error(PDtoMSstatsTMTFormat(input = MSstatsTMT::raw.pd[, !colnames(MSstatsTMT::raw.pd) == "Protein.Accessions"], # missing columns in input - annotation = MSstatsTMT::annotation.pd)) - - expect_error(PDtoMSstatsTMTFormat(input = MSstatsTMT::raw.pd, - annotation = MSstatsTMT::annotation.pd[, !colnames(MSstatsTMT::annotation.pd) == "Condition"])) # missing columns in annotation - -}) - -test_that("MaxQtoMSstatsTMTFormat works", { - - expect_error(MaxQtoMSstatsTMTFormat(evidence = MSstatsTMT::evidence, proteinGroups = MSstatsTMT::proteinGroups, - annotation = MSstatsTMT::annotation.pd)) # wrong annotation file - -}) - -test_that("SpectroMinetoMSstatsTMTFormat works", { - - expect_error(SpectroMinetoMSstatsTMTFormat(input = MSstatsTMT::raw.mine, - annotation = MSstatsTMT::annotation.mine, - summaryforMultipleRows = average)) # wrong argument value - -}) - -test_that("PhilosophertoMSstatsTMTFormat works", { - - input_file_path = system.file("raw_data/Philosopher/msstats.csv", - package = "MSstatsTMT") - annotation_file_path = system.file("raw_data/Philosopher/MSstatsTMT_annotation.csv", - package = "MSstatsTMT") - input = data.table::fread(input_file_path) - annotation = data.table::fread(annotation_file_path) - msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) - expect_equal(nrow(msstats_format), 550) - -}) \ No newline at end of file diff --git a/man/PhilosophertoMSstatsTMTFormat.Rd b/man/PhilosophertoMSstatsTMTFormat.Rd index ee2cc5e79..16f6205ac 100644 --- a/man/PhilosophertoMSstatsTMTFormat.Rd +++ b/man/PhilosophertoMSstatsTMTFormat.Rd @@ -76,9 +76,9 @@ Convert Philosopher (Fragpipe) output to MSstatsTMT format. } \examples{ input_file_path = system.file("tinytest/raw_data/Philosopher/msstats.csv", - package = "MSstatsTMT") + package = "MSstatsConvert") annotation_file_path = system.file("tinytest/raw_data/Philosopher/MSstatsTMT_annotation.csv", - package = "MSstatsTMT") + package = "MSstatsConvert") input = data.table::fread(input_file_path) annotation = data.table::fread(annotation_file_path) msstats_format = PhilosophertoMSstatsTMTFormat(input, annotation) From 3ed95cee8a68ece4fdfa117b3a5a2d2a93605433 Mon Sep 17 00:00:00 2001 From: tonywu1999 Date: Fri, 10 Apr 2026 11:36:35 -0400 Subject: [PATCH 4/5] fix docs --- R/converters_MaxQtoMSstatsTMTFormat.R | 2 +- R/converters_OpenMStoMSstatsTMTFormat.R | 2 +- R/converters_PhilosophertoMSstatsTMTFormat.R | 6 ++++-- R/utils_documentation.R | 4 ++-- inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R | 5 +++-- man/DIANNtoMSstatsFormat.Rd | 2 +- man/DIAUmpiretoMSstatsFormat.Rd | 4 ++-- man/FragPipetoMSstatsFormat.Rd | 4 ++-- man/MaxQtoMSstatsFormat.Rd | 4 ++-- man/MaxQtoMSstatsTMTFormat.Rd | 6 +++--- man/MetamorpheusToMSstatsFormat.Rd | 4 ++-- man/OpenMStoMSstatsFormat.Rd | 4 ++-- man/OpenMStoMSstatsTMTFormat.Rd | 4 ++-- man/OpenSWATHtoMSstatsFormat.Rd | 4 ++-- man/PDtoMSstatsFormat.Rd | 4 ++-- man/PDtoMSstatsTMTFormat.Rd | 4 ++-- man/PhilosophertoMSstatsTMTFormat.Rd | 6 +++--- man/ProgenesistoMSstatsFormat.Rd | 4 ++-- man/ProteinProspectortoMSstatsTMTFormat.Rd | 4 ++-- man/SkylinetoMSstatsFormat.Rd | 2 +- man/SpectroMinetoMSstatsTMTFormat.Rd | 4 ++-- man/SpectronauttoMSstatsFormat.Rd | 4 ++-- man/dot-getPhilosopherInput.Rd | 4 ++++ man/dot-sharedParametersAmongConverters.Rd | 4 ++-- 24 files changed, 51 insertions(+), 44 deletions(-) diff --git a/R/converters_MaxQtoMSstatsTMTFormat.R b/R/converters_MaxQtoMSstatsTMTFormat.R index efb925437..a2b85e308 100644 --- a/R/converters_MaxQtoMSstatsTMTFormat.R +++ b/R/converters_MaxQtoMSstatsTMTFormat.R @@ -6,7 +6,7 @@ #' @param which.proteinid Use 'Proteins' (default) column for protein name. 'Leading.proteins' or 'Leading.razor.proteins' or 'Gene.names' can be used instead to get the protein ID with single protein. However, those can potentially have the shared peptides. #' @param rmProt_Only.identified.by.site TRUE will remove proteins with '+' in 'Only.identified.by.site' column from proteinGroups.txt, which was identified only by a modification site. FALSE is the default. #' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. -#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE. #' @param ... additional parameters to `data.table::fread`. #' @inheritParams .sharedParametersAmongConverters #' diff --git a/R/converters_OpenMStoMSstatsTMTFormat.R b/R/converters_OpenMStoMSstatsTMTFormat.R index 8c4f0f8e6..a5fda7aca 100644 --- a/R/converters_OpenMStoMSstatsTMTFormat.R +++ b/R/converters_OpenMStoMSstatsTMTFormat.R @@ -1,7 +1,7 @@ #' Generate MSstatsTMT required input format for OpenMS output #' @param input MSstatsTMT report from OpenMS #' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. -#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE. #' @param summaryforMultiplePSMs sum(default) or max - when there are multiple measurements for certain feature in certain run, select the feature with the largest summation or maximal value. #' @param ... additional parameters to `data.table::fread`. #' @inheritParams .sharedParametersAmongConverters diff --git a/R/converters_PhilosophertoMSstatsTMTFormat.R b/R/converters_PhilosophertoMSstatsTMTFormat.R index 3bed3ad8a..8f57e8417 100644 --- a/R/converters_PhilosophertoMSstatsTMTFormat.R +++ b/R/converters_PhilosophertoMSstatsTMTFormat.R @@ -13,7 +13,7 @@ #' The probability is confidence score determined by PeptideProphet and higher values indicate greater confidence. #' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. #' @param rmPeptide_OxidationM TRUE (default) will remove the peptides including oxidation (M) sequence. -#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE. #' @param ... additional parameters to `data.table::fread`. #' @inheritParams .sharedParametersAmongConverters #' @@ -102,7 +102,9 @@ PhilosophertoMSstatsTMTFormat = function( #' Convert Philosopher parameters to consistent format -#' @inheritParams PhilosophertoMSstatsTMTFormat +#' @inheritParams PhilosophertoMSstatsTMTFormat +#' @param path character. Path to a file or directory containing msstats.csv output(s) from Philosopher. Used when \code{input} is NULL. +#' @param folder logical. If TRUE, \code{path} is treated as a directory and all msstats files within it are read. If FALSE, \code{path} is treated as a single file path. #' @keywords internal .getPhilosopherInput = function(input, path, folder) { if (!is.null(input)) { diff --git a/R/utils_documentation.R b/R/utils_documentation.R index c734e8f07..3bf208f71 100644 --- a/R/utils_documentation.R +++ b/R/utils_documentation.R @@ -5,7 +5,7 @@ #' @param removeFewMeasurements TRUE (default) will remove the features that have 1 or 2 measurements across runs. #' @param useUniquePeptide TRUE (default) removes peptides that are assigned for more than one proteins. #' We assume to use unique peptide for each protein. -#' @param summaryforMultipleRows max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. +#' @param summaryforMultipleRows max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters. #' @param removeProtein_with1Feature TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default. #' @param removeProtein_with1Peptide TRUE will remove the proteins which have only 1 peptide and charge. FALSE is default. #' @param removeOxidationMpeptides TRUE will remove the peptides including 'oxidation (M)' in modification. FALSE is default. @@ -14,7 +14,7 @@ #' will be saved to a file. #' @param append logical. If TRUE, information about data processing will be added #' to an existing log file. -#' @param verbose logical. If TRUE, information about data processing wil be printed +#' @param verbose logical. If TRUE, information about data processing will be printed #' to the console. #' @param log_file_path character. Path to a file to which information about #' data processing will be saved. diff --git a/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R b/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R index 2adb23209..77ecbcddc 100644 --- a/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R +++ b/inst/tinytest/test_converters_PDtoMSstatsTMTFormat.R @@ -24,10 +24,11 @@ annotation.pd = data.table::fread(system.file("tinytest/raw_data/PDTMT/pd_annota package = "MSstatsConvert")) expect_error(PDtoMSstatsTMTFormat(input = pd_raw[, !colnames(pd_raw) == "Protein.Accessions"], # missing columns in input - annotation = annot)) + annotation = annot, use_log_file = FALSE)) expect_error(PDtoMSstatsTMTFormat(input = pd_raw, - annotation = annot[, !colnames(annot) == "Condition"])) # missing columns in annotation + annotation = annot[, !colnames(annot) == "Condition"], # missing columns in annotation + use_log_file = FALSE)) # Verify output intensities are present in input intensity_cols = grep("^Abundance", colnames(pd_raw), value = TRUE) diff --git a/man/DIANNtoMSstatsFormat.Rd b/man/DIANNtoMSstatsFormat.Rd index eac6e97d9..24cdc0598 100644 --- a/man/DIANNtoMSstatsFormat.Rd +++ b/man/DIANNtoMSstatsFormat.Rd @@ -89,7 +89,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/DIAUmpiretoMSstatsFormat.Rd b/man/DIAUmpiretoMSstatsFormat.Rd index 7badbc326..60ddb5623 100644 --- a/man/DIAUmpiretoMSstatsFormat.Rd +++ b/man/DIAUmpiretoMSstatsFormat.Rd @@ -38,7 +38,7 @@ DIAUmpiretoMSstatsFormat( \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -46,7 +46,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/FragPipetoMSstatsFormat.Rd b/man/FragPipetoMSstatsFormat.Rd index 2b2ed2de6..f2b2e86f4 100644 --- a/man/FragPipetoMSstatsFormat.Rd +++ b/man/FragPipetoMSstatsFormat.Rd @@ -27,7 +27,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -35,7 +35,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/MaxQtoMSstatsFormat.Rd b/man/MaxQtoMSstatsFormat.Rd index f245b63cf..dd22234e9 100644 --- a/man/MaxQtoMSstatsFormat.Rd +++ b/man/MaxQtoMSstatsFormat.Rd @@ -34,7 +34,7 @@ MaxQtoMSstatsFormat( \item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{removeFewMeasurements}{TRUE (default) will remove the features that have 1 or 2 measurements across runs.} @@ -50,7 +50,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/MaxQtoMSstatsTMTFormat.Rd b/man/MaxQtoMSstatsTMTFormat.Rd index cb6eae723..af761b6be 100644 --- a/man/MaxQtoMSstatsTMTFormat.Rd +++ b/man/MaxQtoMSstatsTMTFormat.Rd @@ -37,9 +37,9 @@ We assume to use unique peptide for each protein.} \item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} -\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -47,7 +47,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/MetamorpheusToMSstatsFormat.Rd b/man/MetamorpheusToMSstatsFormat.Rd index 905db7685..1e8851be7 100644 --- a/man/MetamorpheusToMSstatsFormat.Rd +++ b/man/MetamorpheusToMSstatsFormat.Rd @@ -36,7 +36,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -44,7 +44,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/OpenMStoMSstatsFormat.Rd b/man/OpenMStoMSstatsFormat.Rd index 4e68e0055..2f8c39710 100644 --- a/man/OpenMStoMSstatsFormat.Rd +++ b/man/OpenMStoMSstatsFormat.Rd @@ -31,7 +31,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -39,7 +39,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/OpenMStoMSstatsTMTFormat.Rd b/man/OpenMStoMSstatsTMTFormat.Rd index 4b2c94349..b1fddf8f4 100644 --- a/man/OpenMStoMSstatsTMTFormat.Rd +++ b/man/OpenMStoMSstatsTMTFormat.Rd @@ -25,7 +25,7 @@ We assume to use unique peptide for each protein.} \item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} -\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE.} \item{summaryforMultiplePSMs}{sum(default) or max - when there are multiple measurements for certain feature in certain run, select the feature with the largest summation or maximal value.} @@ -35,7 +35,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/OpenSWATHtoMSstatsFormat.Rd b/man/OpenSWATHtoMSstatsFormat.Rd index 6d1c05a16..74ed2a3e2 100644 --- a/man/OpenSWATHtoMSstatsFormat.Rd +++ b/man/OpenSWATHtoMSstatsFormat.Rd @@ -37,7 +37,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -45,7 +45,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/PDtoMSstatsFormat.Rd b/man/PDtoMSstatsFormat.Rd index 4cc066431..40dbe8c05 100644 --- a/man/PDtoMSstatsFormat.Rd +++ b/man/PDtoMSstatsFormat.Rd @@ -34,7 +34,7 @@ Run information. 'Run' will be matched with 'Spectrum.File'.} \item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{removeFewMeasurements}{TRUE (default) will remove the features that have 1 or 2 measurements across runs.} @@ -54,7 +54,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/PDtoMSstatsTMTFormat.Rd b/man/PDtoMSstatsTMTFormat.Rd index f99360b66..6d53ef747 100644 --- a/man/PDtoMSstatsTMTFormat.Rd +++ b/man/PDtoMSstatsTMTFormat.Rd @@ -37,7 +37,7 @@ We assume to use unique peptide for each protein.} \item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -45,7 +45,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/PhilosophertoMSstatsTMTFormat.Rd b/man/PhilosophertoMSstatsTMTFormat.Rd index 16f6205ac..d2c8225a7 100644 --- a/man/PhilosophertoMSstatsTMTFormat.Rd +++ b/man/PhilosophertoMSstatsTMTFormat.Rd @@ -48,9 +48,9 @@ We assume to use unique peptide for each protein.} \item{rmPeptide_OxidationM}{TRUE (default) will remove the peptides including oxidation (M) sequence.} -\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -58,7 +58,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/ProgenesistoMSstatsFormat.Rd b/man/ProgenesistoMSstatsFormat.Rd index 5f3d9ede9..3d4cc7caf 100644 --- a/man/ProgenesistoMSstatsFormat.Rd +++ b/man/ProgenesistoMSstatsFormat.Rd @@ -27,7 +27,7 @@ ProgenesistoMSstatsFormat( \item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{removeFewMeasurements}{TRUE (default) will remove the features that have 1 or 2 measurements across runs.} @@ -41,7 +41,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/ProteinProspectortoMSstatsTMTFormat.Rd b/man/ProteinProspectortoMSstatsTMTFormat.Rd index 1c4383ae2..9e9d49db2 100644 --- a/man/ProteinProspectortoMSstatsTMTFormat.Rd +++ b/man/ProteinProspectortoMSstatsTMTFormat.Rd @@ -32,7 +32,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -40,7 +40,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/SkylinetoMSstatsFormat.Rd b/man/SkylinetoMSstatsFormat.Rd index ae9967189..98248eff3 100644 --- a/man/SkylinetoMSstatsFormat.Rd +++ b/man/SkylinetoMSstatsFormat.Rd @@ -47,7 +47,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/SpectroMinetoMSstatsTMTFormat.Rd b/man/SpectroMinetoMSstatsTMTFormat.Rd index 3a179444b..cca8cb167 100644 --- a/man/SpectroMinetoMSstatsTMTFormat.Rd +++ b/man/SpectroMinetoMSstatsTMTFormat.Rd @@ -36,7 +36,7 @@ We assume to use unique peptide for each protein.} \item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{use_log_file}{logical. If TRUE, information about data processing will be saved to a file.} @@ -44,7 +44,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/SpectronauttoMSstatsFormat.Rd b/man/SpectronauttoMSstatsFormat.Rd index 8c9525d02..dea2e4b99 100644 --- a/man/SpectronauttoMSstatsFormat.Rd +++ b/man/SpectronauttoMSstatsFormat.Rd @@ -75,7 +75,7 @@ We assume to use unique peptide for each protein.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{calculateAnomalyScores}{Default is FALSE. If TRUE, will run anomaly detection model and calculate anomaly scores for each feature. Used downstream to weigh measurements in differential analysis.} @@ -101,7 +101,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about diff --git a/man/dot-getPhilosopherInput.Rd b/man/dot-getPhilosopherInput.Rd index c851ee325..90c64ab34 100644 --- a/man/dot-getPhilosopherInput.Rd +++ b/man/dot-getPhilosopherInput.Rd @@ -8,6 +8,10 @@ } \arguments{ \item{input}{data.frame of \code{msstats.csv} file produced by Philosopher} + +\item{path}{character. Path to a file or directory containing msstats.csv output(s) from Philosopher. Used when \code{input} is NULL.} + +\item{folder}{logical. If TRUE, \code{path} is treated as a directory and all msstats files within it are read. If FALSE, \code{path} is treated as a single file path.} } \description{ Convert Philosopher parameters to consistent format diff --git a/man/dot-sharedParametersAmongConverters.Rd b/man/dot-sharedParametersAmongConverters.Rd index 12c1f29ec..c9e7c6cd7 100644 --- a/man/dot-sharedParametersAmongConverters.Rd +++ b/man/dot-sharedParametersAmongConverters.Rd @@ -12,7 +12,7 @@ \item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.} -\item{summaryforMultipleRows}{max(default) or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities.} +\item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.} \item{removeProtein_with1Feature}{TRUE will remove the proteins which have only 1 feature, which is the combination of peptide, precursor charge, fragment and charge. FALSE is default.} @@ -28,7 +28,7 @@ will be saved to a file.} \item{append}{logical. If TRUE, information about data processing will be added to an existing log file.} -\item{verbose}{logical. If TRUE, information about data processing wil be printed +\item{verbose}{logical. If TRUE, information about data processing will be printed to the console.} \item{log_file_path}{character. Path to a file to which information about From 7c884ac9877db84a05b3a4e1382ca6551603a915 Mon Sep 17 00:00:00 2001 From: tonywu1999 Date: Fri, 10 Apr 2026 12:13:46 -0400 Subject: [PATCH 5/5] fix pd converter for tmt --- R/converters_PDtoMSstatsTMTFormat.R | 6 +++--- man/PDtoMSstatsTMTFormat.Rd | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/R/converters_PDtoMSstatsTMTFormat.R b/R/converters_PDtoMSstatsTMTFormat.R index b5bad061d..1961e26b6 100644 --- a/R/converters_PDtoMSstatsTMTFormat.R +++ b/R/converters_PDtoMSstatsTMTFormat.R @@ -4,9 +4,9 @@ #' @param annotation annotation with Run, Fraction, TechRepMixture, Mixture, Channel, #' BioReplicate, Condition columns or a path to file. Refer to the example 'annotation' for the meaning of each column. #' @param which.proteinid Use 'Protein.Accessions'(default) column for protein name. 'Master.Protein.Accessions' can be used instead to get the protein name with single protein. -#' @param useNumProteinsColumn logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet. +#' @param useNumProteinsColumn logical, TRUE (default) removes shared peptides by information of # Proteins column in PSM sheet. #' @param rmPSM_withfewMea_withinRun TRUE (default) will remove the features that have 1 or 2 measurements within each Run. -#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE. +#' @param rmProtein_with1Feature TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE. #' @param ... additional parameters to `data.table::fread`. #' @inheritParams .sharedParametersAmongConverters #' @@ -48,7 +48,7 @@ PDtoMSstatsTMTFormat <- function( input = MSstatsConvert::MSstatsPreprocess( input, annotation, - feature_columns = c("PeptideSequence", "PrecursorCharge"), + feature_columns = feature_columns, remove_shared_peptides = useUniquePeptide, remove_single_feature_proteins = rmProtein_with1Feature, feature_cleaning = list(remove_features_with_few_measurements = rmPSM_withfewMea_withinRun, diff --git a/man/PDtoMSstatsTMTFormat.Rd b/man/PDtoMSstatsTMTFormat.Rd index 6d53ef747..46a4cc561 100644 --- a/man/PDtoMSstatsTMTFormat.Rd +++ b/man/PDtoMSstatsTMTFormat.Rd @@ -28,14 +28,14 @@ BioReplicate, Condition columns or a path to file. Refer to the example 'annotat \item{which.proteinid}{Use 'Protein.Accessions'(default) column for protein name. 'Master.Protein.Accessions' can be used instead to get the protein name with single protein.} -\item{useNumProteinsColumn}{logical, TURE(default) remove shared peptides by information of # Proteins column in PSM sheet.} +\item{useNumProteinsColumn}{logical, TRUE (default) removes shared peptides by information of # Proteins column in PSM sheet.} \item{useUniquePeptide}{TRUE (default) removes peptides that are assigned for more than one proteins. We assume to use unique peptide for each protein.} \item{rmPSM_withfewMea_withinRun}{TRUE (default) will remove the features that have 1 or 2 measurements within each Run.} -\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Defaut is FALSE.} +\item{rmProtein_with1Feature}{TRUE will remove the proteins which have only 1 peptide and charge. Default is FALSE.} \item{summaryforMultipleRows}{max or sum - when there are multiple measurements for certain feature and certain run, use highest or sum of multiple intensities. Default is max for label-free converters and sum for TMT converters.}