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tonywu1999tonywu1999
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refactor(diann): move q-value filtering to MSstatsClean for DIANN (#116)
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Lines changed: 98 additions & 50 deletions

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‎DESCRIPTION‎

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@@ -14,7 +14,7 @@ License: Artistic-2.0
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Encoding: UTF-8
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LazyData: true
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Roxygen: list(markdown = TRUE)
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RoxygenNote: 7.3.2
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RoxygenNote: 7.3.3
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biocViews: MassSpectrometry, Proteomics, Software, DataImport, QualityControl
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Depends:
2020
R (>= 4.0)

‎R/clean_DIANN.R‎

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@@ -1,14 +1,14 @@
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#' Clean raw Diann files
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#' @param msstats_object an object of class `MSstatsDIANNFiles`.
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#' @param MBR True if analysis was done with match between runs
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#' @param quantificationColumn Use 'FragmentQuantCorrected'(default) column for quantified intensities for DIANN 1.8.x.
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#' Use 'FragmentQuantRaw' for quantified intensities for DIANN 1.9.x.
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#' Use 'auto' for quantified intensities for DIANN 2.x where each fragment intensity is a separate column, e.g. Fr0Quantity.
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#' @inheritParams DIANNtoMSstatsFormat
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#' @return data.table
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#' @importFrom stats na.omit
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#' @keywords internal
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.cleanRawDIANN <- function(msstats_object, MBR = TRUE,
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quantificationColumn = "FragmentQuantCorrected") {
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quantificationColumn = "FragmentQuantCorrected",
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global_qvalue_cutoff = 0.01,
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qvalue_cutoff = 0.01,
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pg_qvalue_cutoff = 0.01) {
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dn_input <- getInputFile(msstats_object, "input")
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dn_input <- data.table::as.data.table(dn_input)
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@@ -28,7 +28,10 @@
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dn_input <- .cleanDIANNProcessFragmentInfo(dn_input, quantificationColumn)
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# Clean and filter data
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dn_input <- .cleanDIANNCleanAndFilterData(dn_input, quantificationColumn)
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dn_input <- .cleanDIANNCleanAndFilterData(dn_input, MBR, quantificationColumn,
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global_qvalue_cutoff,
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qvalue_cutoff,
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pg_qvalue_cutoff)
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# Rename columns
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dn_input <- .cleanDIANNRenameColumns(dn_input, quantificationColumn)
@@ -145,14 +148,50 @@
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#' Clean and filter data by removing unwanted fragments and NA values
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#' @param dn_input data.table input
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#' @param quantificationColumn quantification column name
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#' @inheritParams DIANNtoMSstatsFormat
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#' @return cleaned data.table
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#' @noRd
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.cleanDIANNCleanAndFilterData <- function(dn_input, quantificationColumn) {
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.cleanDIANNCleanAndFilterData <- function(dn_input, MBR, quantificationColumn,
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global_qvalue_cutoff,
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qvalue_cutoff,
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pg_qvalue_cutoff) {
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# Remove NH3 and H2O loss fragments & remove rows with NA in quant column
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dn_input <- dn_input[!grepl("NH3|H2O", FragmentIon) &
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!is.na(get(quantificationColumn))]
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msg = paste0('** Filtering on Q.Value < ', global_qvalue_cutoff)
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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dn_input = dn_input[QValue < global_qvalue_cutoff, ]
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if (MBR) {
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msg = '** MBR was used to analyze the data. Now setting names and filtering'
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msg_1_mbr = paste0('-- LibPGQValue < ', pg_qvalue_cutoff)
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msg_2_mbr = paste0('-- LibQValue < ', qvalue_cutoff)
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dn_input = dn_input[LibPGQValue < pg_qvalue_cutoff, ]
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dn_input = dn_input[LibQValue < qvalue_cutoff, ]
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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getOption("MSstatsLog")("INFO", msg_1_mbr)
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getOption("MSstatsMsg")("INFO", msg_1_mbr)
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getOption("MSstatsLog")("INFO", msg_2_mbr)
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getOption("MSstatsMsg")("INFO", msg_2_mbr)
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# getOption("MSstatsLog")("INFO", "\n")
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} else{
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msg = '** MBR was not used to analyze the data. Now setting names and filtering'
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msg_1 = paste0('-- Filtering on GlobalPGQValue < ', pg_qvalue_cutoff)
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msg_2 = paste0('-- Filtering on GlobalQValue < ', qvalue_cutoff)
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dn_input = dn_input[GlobalPGQValue < pg_qvalue_cutoff, ]
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dn_input = dn_input[GlobalQValue < qvalue_cutoff, ]
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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getOption("MSstatsLog")("INFO", msg_1)
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getOption("MSstatsMsg")("INFO", msg_1)
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getOption("MSstatsLog")("INFO", msg_2)
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getOption("MSstatsMsg")("INFO", msg_2)
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# getOption("MSstatsLog")("INFO", "\n")
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}
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return(dn_input)
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}
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‎R/converters_DIANNtoMSstatsFormat.R‎

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@@ -14,8 +14,7 @@
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#' @param pg_qvalue_cutoff If MBR is false, the qvalue cutoff for the Global.PG.Q.Value
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#' column, i.e. the global q-value for the protein group. If MBR is true, the
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#' qvalue cutoff for the Lib.PG.Q.Value column, i.e. the protein group q-value for
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#' the library created after the first MBR pass. Run should be the same as filename.
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#' Default is 0.01.
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#' the library created after the first MBR pass. Default is 0.01.
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#' @param useUniquePeptide should unique pepties be removed
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#' @param removeFewMeasurements should proteins with few measurements be removed
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#' @param removeOxidationMpeptides should peptides with oxidation be removed
@@ -71,7 +70,10 @@ DIANNtoMSstatsFormat = function(input, annotation = NULL,
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input = MSstatsConvert::MSstatsImport(list(input = input),
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"MSstats", "DIANN")
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input = MSstatsConvert::MSstatsClean(input, MBR = MBR,
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quantificationColumn = quantificationColumn)
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quantificationColumn = quantificationColumn,
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global_qvalue_cutoff = global_qvalue_cutoff,
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qvalue_cutoff = qvalue_cutoff,
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pg_qvalue_cutoff = pg_qvalue_cutoff)
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annotation = MSstatsConvert::MSstatsMakeAnnotation(input, annotation)
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decoy_filter = list(col_name = "ProteinName",
@@ -83,39 +85,6 @@ DIANNtoMSstatsFormat = function(input, annotation = NULL,
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filter = removeOxidationMpeptides,
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drop_column = FALSE)
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msg = paste0('** Filtering on Global Q Value < ', global_qvalue_cutoff)
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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input = input[DetectionQValue < global_qvalue_cutoff, ]
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if (MBR) {
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msg = '** MBR was used to analyze the data. Now setting names and filtering'
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msg_1_mbr = paste0('-- LibPGQValue < ', pg_qvalue_cutoff)
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msg_2_mbr = paste0('-- LibQValue < ', qvalue_cutoff)
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input = input[LibPGQValue < pg_qvalue_cutoff, ]
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input = input[LibQValue < qvalue_cutoff, ]
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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getOption("MSstatsLog")("INFO", msg_1_mbr)
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getOption("MSstatsMsg")("INFO", msg_1_mbr)
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getOption("MSstatsLog")("INFO", msg_2_mbr)
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getOption("MSstatsMsg")("INFO", msg_2_mbr)
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# getOption("MSstatsLog")("INFO", "\n")
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} else{
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msg = '** MBR was not used to analyze the data. Now setting names and filtering'
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msg_1 = paste0('-- Filtering on GlobalPGQValue < ', pg_qvalue_cutoff)
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msg_2 = paste0('-- Filtering on GlobalQValue < ', qvalue_cutoff)
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input = input[GlobalPGQValue < pg_qvalue_cutoff, ]
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input = input[GlobalQValue < qvalue_cutoff, ]
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getOption("MSstatsLog")("INFO", msg)
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getOption("MSstatsMsg")("INFO", msg)
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getOption("MSstatsLog")("INFO", msg_1)
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getOption("MSstatsMsg")("INFO", msg_1)
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getOption("MSstatsLog")("INFO", msg_2)
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getOption("MSstatsMsg")("INFO", msg_2)
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# getOption("MSstatsLog")("INFO", "\n")
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}
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feature_columns = c("PeptideSequence", "PrecursorCharge",
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"FragmentIon", "ProductCharge")
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input = MSstatsConvert::MSstatsPreprocess(

‎inst/tinytest/test_clean_DIANN.R‎

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@@ -25,3 +25,14 @@ output = MSstatsConvert:::.cleanRawDIANN(input)
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output = MSstatsConvert:::.cleanRawDIANN(input, quantificationColumn = "FragmentQuantRaw")
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.validateOutput(output)
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# Q-value filtering
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output = MSstatsConvert:::.cleanRawDIANN(input, global_qvalue_cutoff = 0.005)
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expect_equal(sum(output$DetectionQValue < 0.005), nrow(output))
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output = MSstatsConvert:::.cleanRawDIANN(input, qvalue_cutoff = 0.00001)
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expect_equal(sum(output$LibQValue < 0.00001), nrow(output))
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output = MSstatsConvert:::.cleanRawDIANN(input, pg_qvalue_cutoff = 0.001)
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expect_equal(sum(output$LibPGQValue < 0.001), nrow(output))
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output = MSstatsConvert:::.cleanRawDIANN(input, MBR = TRUE, qvalue_cutoff = 0.005)
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expect_equal(sum(output$LibQValue < 0.005), nrow(output))
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output = MSstatsConvert:::.cleanRawDIANN(input, MBR = TRUE, pg_qvalue_cutoff = 0.001)
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expect_equal(sum(output$LibPGQValue < 0.001), nrow(output))

‎man/DIANNtoMSstatsFormat.Rd‎

Lines changed: 1 addition & 2 deletions
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‎man/MSstatsClean.Rd‎

Lines changed: 16 additions & 2 deletions
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‎man/dot-cleanRawDIANN.Rd‎

Lines changed: 17 additions & 1 deletion
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