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.
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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) constructExpPseudoSpectra Create a list of all pseudospectra found in a GC-MS experiment of several samples. createSTDdbGC Create an in-house database for GC-MS annotation createSTDdbLC Create an in-house database for LC-MS annotation 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 (GC-MS). 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
runLC - in-house databases are created by functions
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 <email@example.com>
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