Introduction:

This tool is a wrapper for the function 'runLC()' in the R 'metaMS' package. It is designed to process a series of LC-MS data files and to produce a peak table with mz, rt, and intensities of peaks in all samples. The popular package xcms is used to perform the peak picking, grouping and retention correction, peak filling and annotate isotope operations.

Input files:

1.      Multiple LC-MS raw data files in netCDF, mzXML or mzML format.

Parameter£º

1.        RT range: RT range to process in minutes, for example, 5,25.

2.        MZ range option: MZ range retained for the analysis, for example, 50,500.

3.        matchedFilter: Method to use for peak detection. This function identifies peaks in the chromatographic time domain. The intensity values are binned by cutting the LC/MS data into slices (bins) of a mass unit (binSize m/z) wide. Within each bin, the maximal intensity is selected. The peak detection is then performed in each bin by extending it based on the steps parameter to generate slices comprising bins current _bin - steps +1 to current _bin + steps - 1. Each of these slices is then filtered with matched filtration using a second-derivative Gaussian as the model peak shape. After filtration peaks are detected using a signal-to-ration cut-off.

4.        step size: The peak detection algorithm creates extracted base peak chromatograms (EIBPC) on a fixed step size.

5.        FWHM: Full width at half maximum of matched filtration gaussian model peak. Can only be used to calculate the actual sigma.

6.        max: Maximum number of peak per extracted ion chromatogram.

7.        snthresh: Signal to noise ratio cutoff.

8.        min. class. Fraction: Minimum fraction of sample necessary in at least one of the sample groups for it to be a valid group.

9.        min. class. Size: Minimum number of sample necessary in at least one of the sample groups for it to be a valid group.

10.    mzwid: Width of overlapping m/z slices to use for creating peak density chromatograms and grouping peaks across samples.

11.    bws: The two bandwidths used for grouping before and after retention time alignment.

12.    missing ratio: Ratio of missing samples to allow in retention time correction groups.

13.    extra ratio: Ratio of extra peaks to allow in retention time correction groups.

14.    centWave: Method to use for peak detection. The centWave algorithm performs peak density and wavelet-based chromatographic peak detection. It is most suitable for high-resolution LC/{TOF,OrbiTrap,FTICR}-MS data in centroid mode. In the first phase the method identifies regions of interest (ROIs) representing mass traces that are characterized as regions with less than ppm m/z deviation in consecutive scans in the LC/MS map. These ROIs are then subsequently analyzed using continuous wavelet transform (CWT) to locate chromatographic peaks on different scales. The first analysis step is skipped, if regions of interest are passed via the param parameter.

15.    ppm: Numeric defining the maximal tolerated m/z deviation in consecutive scans in parts per million (ppm) for the initial ROI definition

16.    peakwidth: numeric with the expected approximate peak width in chromatographic space. Given as a range (min, max) in seconds.

17.    prefilter:  numeric: c (k, I) specifying the prefilter step for the first analysis step (ROI detection). Mass traces are only retained if they contain at least k peaks with intensity >= I.

Output files:

1.      'lcms_raw_pkTable.txt', a peak table is generated with one line per "compound" and one column per sample.

For example:

ID

isotopes

mz

rt

wt15

wt16

wt18

1

 

252.972599324339

0.618895273997614

144.509189798977

343.376682587947

198.534228156601

2

 

236.996474292009

0.923942096017473

21.4248698000488

43.7274752957502

24.8619526761885

3

 

1042.19326334764

10.7589117905883

166.606206029299

306.409056911838

274.304079140729

4

[4][M]+

344.916924035475

10.7591648568759

22.611706846678

55.3782337963919

46.4583599456847

5

 

273.076338594995

18.2270447644806

212.660961653673

225.587440278514

226.596054810798

2.      'lcms_isotopes_removed_pkTable.txt', isotopes removed peak table.

ID

mz

rt

wt15

wt16

wt18

1

252.972599324339

0.618895273997614

144.509189798977

343.376682587947

198.534228156601

2

236.996474292009

0.923942096017473

21.4248698000488

43.7274752957502

24.8619526761885

3

1042.19326334764

10.7589117905883

166.606206029299

306.409056911838

274.304079140729

4

344.916924035475

10.7591648568759

22.611706846678

55.3782337963919

46.4583599456847

5

273.076338594995

18.2270447644806

212.660961653673

225.587440278514

226.596054810798

3.      'lcms_isotopes_removed_pkTable.txt', isotopes removed peak table.

4.      'raw_tics.pdf', raw total ion chromatograms.

5.      'raw_bpcs.pdf', raw base peak chromatograms.

6.      'rtcorrected_tics.pdf', RT corrected total ion chromatograms.

7.      'rtcorrected_bpcs.pdf', RT corrected base peak chromatograms.

8.      'rt_deviation_plot.pdf', plot about RT deviation.

9.      'EICs', Extracted Ion Chromatograms.

Note£º

Here ProteoWizard software (http://proteowizard.sourceforge.net/doc_users.html) is recommended for converting raw data files from various instrument vendors to mzXML format. It supports the reading/writing of the following open formats on all platforms (note: vendor formats require Windows with vendor libraries).

mzML 1.1

mzML 1.0

mzXML

MGF

MS2/CMS2/BMS2

mzIdentML

 

Please read the protocol of this software carefully. It can not be used for any commercial purposes.

Reference:

[1]     R. Wehrens, G. Weingart and F. Mattivi, metaMS: An open-source pipeline for GC-MS-based untargeted metabolomics J. Chrom. B (2014), v966, 109-116.

[2]     Colin A. Smith, Elizabeth J. Want, Grace O¡¯Maille, Ruben Abagyan and Gary Siuzdak. "XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification" Anal. Chem. 2006, 78:779-787.

[3]     Ralf Tautenhahn, Christoph B\"ottcher, and Steffen Neumann "Highly sensitive feature detection for high-resolution LC/MS" BMC Bioinformatics 2008, 9:504

[4]     Chambers M C, Maclean B, Burke R, et al. A cross-platform toolkit for mass spectrometry and proteomics[J]. Nature Biotechnology, 2012, 30(10):918-920.http://proteowizard.sourceforge.net/doc_users.html