Closed:how can i import a Mass spectrometry data in R
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Nemo ▴ 80
Last seen 6.4 years ago

I have a proteomics data with format .RAW

then I converted it to mzXML by proteoWizard. Now I want to load it and search for proteins etc 

There are few ways which none could help me go through the data 

for example 

file <- list.files("path to my data", pattern="mydata.mzXML",full.names=TRUE, recursive = TRUE)
raws <- readMSData(file, verbose=FALSE)

this gives me  the following 

Object of class "MSnExp"
 Object size in memory: 1870.38 Mb
- - - Spectra data - - -
 MS level(s): 2 
 Number of MS1 acquisitions: 5428 
 Number of MSn scans: 25855 
 Number of precursor ions: 25855 
 25736 unique MZs
 Precursor MZ's: 350.19 - 1549.6 
 MSn M/Z range: 99 6062.42 
 MSn retention times: 3:56 - 133:58 minutes
- - - Processing information - - -
Data loaded: Thu Sep 24 15:11:54 2015 
 MSnbase version: 1.16.2 
- - - Meta data  - - -
  rowNames: 1
  varLabels: sampleNames
  varMetadata: labelDescription
protocolData: none
  featureNames: X1.1 X10.1 ... X9999.1 (25855 total)
  fvarLabels: spectrum
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'

however when I use another way to import the data I get the following information 

mzf <- file.path("path to the data", pattern="my data.mzXML")
> ms <- openMSfile(mzf)
> hd <- header(ms)
> dim(hd)
[1] 42785    21
> names(hd)
 [1] "seqNum"                   "acquisitionNum"           "msLevel"                  "polarity"                 "peaksCount"               "totIonCurrent"           
 [7] "retentionTime"            "basePeakMZ"               "basePeakIntensity"        "collisionEnergy"          "ionisationEnergy"         "lowMZ"                   
[13] "highMZ"                   "precursorScanNum"         "precursorMZ"              "precursorCharge"          "precursorIntensity"       "mergedScan"              
[19] "mergedResultScanNum"      "mergedResultStartScanNum" "mergedResultEndScanNum" 

they are different in dim. WHY?

is there a way to import data directly from .RAW ?

if no, which software is the best to convert the data into a format which I will be sure that i am not losing any information ?


Many thanks 


r proteomics RforProteomics • 447 views
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