metaMS-package: Analysis pipeline for MS-based metabolomics data

metaMS-packageR Documentation

Analysis pipeline for MS-based metabolomics data


Analysis pipeline for MS-based metabolomics data: basic peak picking and grouping is done using functions from packages xcms and CAMERA. The main output is a table of feature intensities in all samples, which can immediately be analysed with multivariate methdos. The package supports the creation of in-house databases of mass spectra (including retention information) of pure chemical compounds. Such databases can then be used for annotation purposes.



AnnotateFeature         Feature Wise Annotation
AnnotateTable           AnnotateTable
FEMsettings             FEM Settings for 'metaMS'
LCDBtest                Sample DB for LC-MS annotation
alignmentLC             LC alignment
construct.msp           Functions to handle msp-type objects (GC-MS)
                        Create a list of all pseudospectra found in a
                        GC-MS experiment of several samples.
createSTDdbGC           Create an in-house database for GC-MS
createSTDdbLC           Create an in-house database for LC-MS
exptable                Sample table for DB generation (LC)
generateStdDBGC         Convert an msp object into a GC database object
getAnnotationLC         get LC annotation
getAnnotationMat        Subfunction GC-MS processing
getFeatureInfo          Construct an object containing all
                        meta-information of the annotated pseudospectra
getPeakTable            get peak table
matchExpSpec            Match a GC-MS pseudospectrum to a database with
                        a weighted crossproduct criterion.
matchSamples2DB         Match pseudospectra from several samples to an
                        in-house DB (GC-MS)
matchSamples2Samples    Compare pseudospectra across samples (GC-MS)
peakDetection           Wrapper for XCMS peak detection, to be used for
                        both GC-MS and LC-MS data.
plotPseudoSpectrum      Plot a pseudospectrum.
processStandards        Process input files containing raw data for
                        pure standards.
readStdInfo             Read information of injections of standards
                        from a csv file.
runCAMERA               Run CAMERA
runGC                   Wrapper for processing of GC-MS data files
runLC                   Wrapper for processing of LC-MS data files
treat.DB                Scaling of pseudospectra in an msp object.

The most important functions for running the pipeline are runGC and runLC - in-house databases are created by functions createSTDdbGC and createSTDdbLC.


Ron Wehrens [aut, cre] (author of GC-MS part), Pietro Franceschi [aut] (author of LC-MS part), Nir Shahaf [ctb], Matthias Scholz [ctb], Georg Weingart [ctb] (development of GC-MS approach), Elisabete Carvalho [ctb] (testing and feedback of GC-MS pipeline)

Maintainer: Ron Wehrens <>

rwehrens/metaMS documentation built on Feb. 27, 2023, 5:13 a.m.