readProteomeDiscovererFile {wrProteo}

Read Tabulated Files Exported By ProteomeDiscoverer At Protein Level

Description

Protein identification and quantification results from Thermo ProteomeDiscoverer which were exported as tabulated text can be imported and relevant information extracted.

Usage

readProteomeDiscovererFile(
  fileName,
  path = NULL,
  normalizeMeth = "median",
  sampleNames = NULL,
  read0asNA = TRUE,
  quantCol = "^Abundance",
  annotCol = NULL,
  contamCol = "Contaminant",
  refLi = NULL,
  separateAnnot = TRUE,
  FDRCol = list(c("^Protein.FDR.Confidence", "High"), c("^Found.in.Sample.", "High")),
  gr = NULL,
  sdrf = NULL,
  suplAnnotFile = TRUE,
  groupPref = list(lowNumberOfGroups = TRUE),
  specPref = c(conta = "CON_|LYSC_CHICK", mainSpecies = "OS=Homo sapiens"),
  plotGraph = TRUE,
  wex = 1.6,
  titGraph = "Proteome Discoverer",
  silent = FALSE,
  debug = FALSE,
  callFrom = NULL
)

Arguments

fileName

(character) name of file to be read

path

(character) path of file to be read

normalizeMeth

(character) normalization method, defaults to median, for more details see normalizeThis)

sampleNames

(character) custom column-names for quantification data (ProteomeDiscoverer does not automatically use file-names from spectra); this argument has priority over suplAnnotFile

read0asNA

(logical) decide if initial quntifications at 0 should be transformed to NA

quantCol

(character or integer) define ywhich columns should be extracted as quantitation data : The argument may be the exact column-names to be used, or if length=1 content of quantCol will be used as pattern to search among column-names for $quant using grep; if quantCol='allAfter_calc.pI' all columns to the right of the column 'calc.pI' will be interpreted as quantitation data (may be useful with files that have been manually edited before passing to wrProteo)

annotCol

(character) column names to be read/extracted for the annotation section (default c("Accession","Description","Gene","Contaminant","Sum.PEP.Score","Coverage....","X..Peptides","X..PSMs","X..Unique.Peptides", "X..AAs","MW..kDa.") )

contamCol

(character or integer, length=1) which columns should be used for contaminants marked by ProteomeDiscoverer. If a column named contamCol is found, the data will be lateron filtered to remove all contaminants, set to NULL for keeping all contaminants

refLi

(character or integer) custom specify which line of data is main species, if character (eg 'mainSpe'), the column 'SpecType' in $annot will be searched for exact match of the (single) term given

separateAnnot

(logical) if TRUE output will be organized as list with $annot, $abund for initial/raw abundance values and $quant with final log2 (normalized) quantitations

FDRCol

(list) optional indication to search for protein FDR information

gr

(character or factor) custom defined pattern of replicate association, will override final grouping of replicates from sdrf and/or suplAnnotFile (if provided)

sdrf

(character, list or data.frame) optional extraction and adding of experimenal meta-data: if character, this may be the ID at ProteomeExchange, the second & third elements may give futher indicatations for automatic organization of groups of replicates. Besides, the output from readSdrf or a list from defineSamples may be provided; if gr is provided, gr gets priority for grouping of replicates; if sdrfOrder=TRUE the output will be put in order of sdrf

suplAnnotFile

(logical or character) optional reading of supplemental files produced by ProteomeDiscoverer; however, if gr is provided, gr gets priority for grouping of replicates; if TRUE defaults to file '*InputFiles.txt' (needed to match information of sdrf) which can be exported next to main quantitation results; if character the respective file-name (relative or absolute path)

groupPref

(list) additional parameters for interpreting meta-data to identify structure of groups (replicates), will be passed to readSampleMetaData. May contain lowNumberOfGroups=FALSE for automatically choosing a rather elevated number of groups if possible (defaults to low number of groups, ie higher number of samples per group)

specPref

(character or list) define characteristic text for recognizing (main) groups of species (1st for comtaminants - will be marked as 'conta', 2nd for main species- marked as 'mainSpe', and optional following ones for supplemental tags/species - maked as 'species2','species3',...); if list and list-element has multiple values they will be used for exact matching of accessions (ie 2nd of argument annotCol)

plotGraph

(logical or integer) optional plot of type vioplot of initial and normalized data (using normalizeMeth); if integer, it will be passed to layout when plotting

wex

(integer) relative expansion factor of the violin-plot (will be passed to vioplotW)

titGraph

(character) custom title to plot of distribution of quantitation values

silent

(logical) suppress messages

debug

(logical) additional messages for debugging

callFrom

(character) allow easier tracking of messages produced

Details

This function has been developed using Thermo ProteomeDiscoverer versions 2.2 to 2.5. The format of resulting files at export also depends which columns are chosen as visible inside ProteomeDiscoverer and subsequently get chosen for export. Using the argument suplAnnotFile it is possible to specify a specific file (or search for default file) to read for extracting file-names as sample-names and other experiment realted information. If a column named contamCol is found, the data will be lateron filtered to remove all contaminants, set to NULL for keeping all contaminants.

The final output is a list containing as (main) elements: $annot, $raw and optional $quant, or returns data.frame with entire content of file if separateAnnot=FALSE.

This function replaces the depreciated function readProtDiscovFile.

Value

This function returns a list with $raw (initial/raw abundance values), $quant with final normalized quantitations, $annot, $counts an array with number of peptides, $quantNotes and $notes; or if separateAnnot=FALSE the function returns a data.frame with annotation and quantitation only

See Also

read.table, normalizeThis) , readMaxQuantFile, readProlineFile, readFragpipeFile

Examples

path1 <- system.file("extdata", package="wrProteo")
fiNa <- "tinyPD_allProteins.txt.gz"
dataPD <- readProteomeDiscovererFile(file=fiNa, path=path1, suplAnnotFile=FALSE)
summary(dataPD$quant)