readProlineFile: Read csv or txt files exported from Proline and MS-Angel

Description

Quantification results form MS-Angel and Proline Proline exported as xlsx format can be read directly. Besides, files in tsv, csv (European and US format) or tabulated txt can be read, too. Then relevant information gets extracted, the data can optionally normalized and displayed as boxplot or vioplot. The final output is a list containing 6 elements: $raw, $quant, $annot, $counts, $quantNotes and $notes. Alternatively, a data.frame with annotation and quantitation data may be returned if separateAnnot=FALSE. Note: There is no normalization by default since quite frequently data produced by Proline are already sufficiently normalized. The figure produced using the argument plotGraph=TRUE may help judging if the data appear sufficiently normalized (distribtions should align).

Usage

readProlineFile(
  fileName,
  path = NULL,
  normalizeMeth = NULL,
  logConvert = TRUE,
  sampleNames = NULL,
  quantCol = "^abundance_",
  annotCol = c("accession", "description", "is_validated", "protein_set_score",
    "X.peptides", "X.specific_peptides"),
  remStrainNo = TRUE,
  pepCountCol = c("^psm_count_", "^peptides_count_"),
  trimColnames = FALSE,
  refLi = NULL,
  separateAnnot = TRUE,
  plotGraph = TRUE,
  tit = NULL,
  graphTit = NULL,
  wex = 2,
  specPref = c(conta = "_conta\\|", mainSpecies = "OS=Homo sapiens"),
  silent = FALSE,
  callFrom = NULL,
  debug = FALSE
)

Arguments

fileName

(character) name of file to read; .xlsx-, .csv-, .txt- and .tsv can be read (csv, txt and tsv may be gz-compressed). Reading xlsx requires package 'readxl'.

path

(character) optional path (note: Windows backslash sould be protected or written as '/')

normalizeMeth

(character) normalization method (for details and options see normalizeThis)

logConvert

(logical) convert numeric data as log2, will be placed in $quant

sampleNames

(character) new column-names for quantification data (ProteomeDiscoverer does not automatically use file-names from spectra); Please use with care since order of samples might be different as you expect

quantCol

(character or integer) colums with main quantitation-data : precise colnames to extract, or if length=1 content of quantCol will be used as pattern to search among column-names for $quant using grep

annotCol

(character) precise colnames or if length=1 pattern to search among column-names for $annot

remStrainNo

(logical) if TRUE, the organism annotation will be trimmed to uppercaseWord+space+lowercaseWord (eg Homo sapiens)

pepCountCol

(character) pattern to search among column-names for count data of PSM and NoOfPeptides

trimColnames

(logical) optional trimming of column-names of any redundant characters from beginning and end

refLi

(integer) custom decide which line of data is main species, if single character entry it will be used to choose a group of species (eg 'mainSpe')

separateAnnot

(logical) separate annotation form numeric data (quantCol and annotCol must be defined)

plotGraph

(logical or matrix of integer) optional plot vioplot of initial data; if integer, it will be passed to layout when plotting

tit

(character) custom title to plot

graphTit

(character) (depreciated custom title to plot), please use 'tit'

wex

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

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)

silent

(logical) suppress messages

callFrom

(character) allow easier tracking of message(s) produced

debug

(logical) display additional messages for debugging

Value

list with $raw (initial/raw abundance values), $quant with final normalized quantitations, $annot (columns ), $counts an array with 'PSM' and 'NoOfPeptides', $quantNotes and $notes; or a data.frame with quantitation and annotation if separateAnnot=FALSE

Details

This function has been developed using Proline version 1.6.1 coupled with MS-Angel 1.6.1. The classical way of using ths function consists in exporting results produced by Proline and MS-Angel as xlsx file. Besides, other formats may be read, too. This includes csv (eg the main sheet/table of ths xlsx exported file saved as csv). WOMBAT represents an effort to automatize quantitative proteomics experiments, using this route data get exported as txt files which can be read, too.

Examples

Run this code

# NOT RUN {
path1 <- system.file("extdata", package="wrProteo")
fiNa <- "exampleProlineABC.csv.gz"
dataABC <- readProlineFile(file.path(path1, fiNa))
summary(dataABC$quant)
# }