Quantification results using MassChroQ should be initially treated using the R-package MassChroqR (both distributed by the PAPPSO at http://pappso.inrae.fr/) for initial normalization on peptide-level and combination of peptide values into protein abundances.
readMassChroQFile(
fileName,
path = NULL,
normalizeMeth = "median",
sampleNames = NULL,
refLi = NULL,
separateAnnot = TRUE,
titGraph = "MassChroQ",
wex = NULL,
specPref = c(conta = "CON_|LYSC_CHICK", mainSpecies = "OS=Homo sapiens"),
gr = NULL,
sdrf = NULL,
suplAnnotFile = FALSE,
groupPref = list(lowNumberOfGroups = TRUE, chUnit = TRUE),
plotGraph = TRUE,
silent = FALSE,
debug = FALSE,
callFrom = NULL
)
This function returns 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
(character) name of file to be read (may be tsv, csv, rda or rdata); both US and European csv formats are supported
(character) path of file to be read
(character) normalization method (will be sent to normalizeThis
)
(character) custom column-names for quantification data; this argument has priority over suplAnnotFile
(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
(logical) if TRUE
output will be organized as list with $annot
, $abund
for initial/raw abundance values and $quant
with final normalized quantitations
(character) custom title to plot of distribution of quantitation values
(integer) relative expansion factor of the violin-plot (will be passed to vioplotW
)
(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
)
(character or factor) custom defined pattern of replicate association, will override final grouping of replicates from sdrf
and/or suplAnnotFile
(if provided)
(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
(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)
(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)
May contain chUnit
(logical or character) to be passed to readSampleMetaData()
for (optional) adjustig of unit-prefixes in meta-data group labels, in case multiple different unit-prefixes
are used (eg '100pMol' and '1nMol').
(logical) optional plot of type vioplot of initial and normalized data (using normalizeMeth
); if integer, it will be passed to layout
when plotting
(logical) suppress messages
(logical) additional messages for debugging
(character) allow easier tracking of messages produced
The final output of this fucntion is a list containing 3 elements: $annot
, $raw
, $quant
and $notes
, or returns data.frame with entire content of file if separateAnnot=FALSE
. Other list-elements remain empty to keep format compatible to other import functions.
This function has been developed using MassChroQ version 2.2 and R-package MassChroqR version 0.4.0. Both are distributed by the PAPPSO (http://pappso.inrae.fr/). When saving quantifications generated in R as RData (with extension .rdata or .rda) using the R-packages associated with MassChroq, the ABUNDANCE_TABLE produced by mcq.get.compar(XICAB) should be used.
After import data get (re-)normalized according to normalizeMeth
and refLi
, and boxplots or vioplots drawn.
read.table
, normalizeThis
) , readProlineFile
path1 <- system.file("extdata", package="wrProteo")
fiNa <- "tinyMC.RData"
dataMC <- readMassChroQFile(file=fiNa, path=path1)
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