enviPick (version 1.2)

enviPick-package: Peak picking for high resolution liquid chromatography - mass spectrometry (LC-HRMS) data

Description

Peak picking for centroided and baseline-corrected high-resolution LC-MS data.mzXML. Built on a three-step approach of (1) data partitioning, (2) unsupervised clustering of extracted ion chromatograms (EIC) and (3) shape-independent peak detection wihtin individual EICs. Interactive plot access to all results and the underlying raw measurements. Browser UI for non-R users. Batch processing.

Warning

This package has only been tested on HIGH-RESOLUTION Thermo Orbitrap and QExactive measurements processed (centroided) with ProteoWizard`s MSConvert. It may not give satisfying results for chromatograms affected by mass shifts from centroid-centroid interferences prevalent at low resolutions.

Details

ll{ Package: enviPick Type: Package Version: 1.0 Date: 2014-14-07 License: GPL-2 } After initial upload of an .mzXML file with readMSdata, above steps (1) to (3) are calculated by mzagglom, mzclust and mzpick, respectively. The wrapper for joint upload and processing is enviPickwrap. The raw data and the results of each step, a so-called MSlist object, can be viewed by plotMSlist, producing an interactive plot that conveniently offers zoom, drag and select functionality and easy identification of individual partitions, EIC cluster or peaks. Batch processing can be done via enviPickbatch. To export a peak list from an MSlist object, use writePeaklist. For converting LC-HRMS measurement files from various vendor formats or .mzML to centroided .mzXML we strongly recommend the MSConvert tool from ProteoWizard; for centroidization choose Filters -> Peak Picking -> Prefer Vendor -> Add.

References

Loos, M. (XXXX). Extraction of ion chromatograms by unsupervised clustering of high-resolution mass spectrometry data. Some Journal. Sometime. ProteoWizard: Open Source Software for Rapid Proteomics Tools Development Darren Kessner; Matt Chambers; Robert Burke; David Agus; Parag Mallick Bioinformatics 2008 http://proteowizard.sourceforge.net/

See Also

readMSdata mzagglom mzpart mzclust mzpick plotMSlist enviPickwrap enviPickbatch

Examples

##################################################
# (1) Define path to an LC-HRMS .mzML file (not provided with package):

filepath.mzML<-"C:/.../2012_07_01.mzML"

# (2) Initialize an MSlist object and load this .mzML file into it:

MSlist<-readMSdata(filepath.mzML, MSlevel=c(1))

# (3) Partition the measurements now available in MSlist:

MSlist<-mzagglom(MSlist,dmzgap=10,ppm=TRUE,drtgap=500,minpeak=4,maxint=1E7)

# (4) EIC clustering of the partitions now available in MSlist:

MSlist<-mzclust(MSlist,dmzdens=5,ppm=TRUE,drtdens=120,minpeak=4)      

# (5) Peak picking within the EIC clusters now available in MSlist:

MSlist<-mzpick(MSlist, minpeak = 4, drtsmall = 50, drtfill = 10,  drttotal = 200, recurs = 4, 
	weight = 2, SB = 3, SN=2, minint = 1E4, maxint = 1e+07, ended = 2)

# (6) Export a peak list now available in MSlist:

writePeaklist(MSlist,"directory","filename")

# (7) View your partitioning / EIC clustering / peak picking results:

plotMSlist(MSlist,ppmbar=10);
##################################################

##################################################
# Do above steps (1) to (5) in one wrap, then export a peak list:

MSlist<-enviPickwrap( filepath.mzML,
                      MSlevel=c(1),
                      dmzgap=10,  
                      dmzdens=5,       
                      ppm=TRUE,
                      drtgap=1000, 
                      drtsmall=20,
                      drtdens=250,
                      drtfill=10,
                      drttotal=200,
                      minpeak=4,
                      recurs=10,
                      weight=2,
                      SB=3,
                      SN=2,
                      minint=10E4,
                      maxint=10E6,
                      ended=2,
                      progbar=TRUE
                       )
					   
writePeaklist(MSlist,"directory","filename")
##################################################