Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

---

Documentation for package ‘msPurity’ version 1.26.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

assessPuritySingle	Assess the purity of a single LC-MS/MS or DI-MS/MS file
averageAllFragSpectra	Using a purityA object, average and filter MS/MS spectra for each XCMS feature within and across MS data files (ignoring intra and inter relationships)
averageAllFragSpectra-method	Using a purityA object, average and filter MS/MS spectra for each XCMS feature within and across MS data files (ignoring intra and inter relationships)
averageInterFragSpectra	Using a purityA object, average and filter fragmentation spectra for each XCMS feature across multiple MS data files
averageInterFragSpectra-method	Using a purityA object, average and filter fragmentation spectra for each XCMS feature across multiple MS data files
averageIntraFragSpectra	Using a purityA object, average and filter fragmentation spectra for each XCMS feature within a MS data file
averageIntraFragSpectra-method	Using a purityA object, average and filter fragmentation spectra for each XCMS feature within a MS data file
averageSpectra	Using purityD object, calculates to average mz, intensity and signal-to-noise of multiple scans from multiple MS datafiles (mzML or .csv)
averageSpectra-method	Using purityD object, calculates to average mz, intensity and signal-to-noise of multiple scans from multiple MS datafiles (mzML or .csv)
averageSpectraSingle	Calculates to average mz, intensity and signal-to-noise of multiple scans from 1 MS datafile (mzML or .csv)
combineAnnotations	Combine Annotations
createDatabase	Create database
createMSP	Using a purityA object, create an MSP file of fragmentation spectra
createMSP-method	Using a purityA object, create an MSP file of fragmentation spectra
create_database	Create database deprecated
dimsPredictPurity	Using purityD object, assess anticipated purity from a DI-MS run
dimsPredictPurity-method	Using purityD object, assess anticipated purity from a DI-MS run
dimsPredictPuritySingle	Predict the precursor purity from a DI-MS dataset
filterFragSpectra	Filter fragmentation spectra associated with an XCMS feature
filterFragSpectra-method	Filter fragmentation spectra associated with an XCMS feature
filterp	Filter out peaks based on intensity and RSD criteria
filterp-method	Filter out peaks based on intensity and RSD criteria
flag_remove	Flag and remove unwanted peaks
frag4feature	Using a purityA object, link MS/MS data to XCMS features
frag4feature-method	Using a purityA object, link MS/MS data to XCMS features
Getfiles	Get files for DI-MS processing
getP	Get peaklist for a purityD object
getP-method	Get peaklist for a purityD object
get_additional_mzml_meta	Get additional mzML meta
groupPeaks	Using purityD object, group multiple peaklists by similar mz values (mzML or .csv)
groupPeaks-method	Using purityD object, group multiple peaklists by similar mz values (mzML or .csv)
groupPeaksEx	Group peaklists from a list of dataframes
initialize-method	Constructor for S4 class to represent a DI-MS purityD
iwNormGauss	Gaussian normalisation for isolation window efficiency
iwNormQE.5	Q-Exactive +/- 0.5 range, normalisation for isolation window efficiency
iwNormRcosine	Raised cosine normalisation for isolation window efficiency
msPurity	'msPurity' package
pcalc	Perform purity calculation on a peak matrix
purityA	Assess the acquired precursor ion purity of MS/MS spectra (constructor)
purityD	An S4 class to represent a DI-MS purityD
purityD-class	An S4 class to represent a DI-MS purityD
purityX	Assessing anticipated purity of XCMS features from an LC-MS run
show-method	Show method for purityA class
show-method	Show method for purityD
show-method	Show method for purityX
spectralMatching	Spectral matching for LC-MS/MS datasets
spectral_matching	Spectral matching deprecated
subtract	Using Subtract MZ values based on ppm tolerance and noise ratio
subtract-method	Using Subtract MZ values based on ppm tolerance and noise ratio
subtractMZ	Subtract MZ values based on ppm tolerance and noise ratio
validate	Validate precursor purity predictions using LC-MS and LC-MS/MS dataset
validate-method	Validate precursor purity predictions using LC-MS and LC-MS/MS dataset
writeOut	Using purityD object, save peaks as text files
writeOut-method	Using purityD object, save peaks as text files