do.findmain: do.findmain

In sneumann/RAMClustR: RAMClust: a novel feature clustering method enables spectral-matching based annotation for metabolomics data

Description

Cluster annotation function: inference of 'M' - molecular weight of the compound giving rise to each spectrum - using the InterpretMSSpectrum::findMain function

Usage

do.findmain(ramclustObj = RC, cmpd = NULL, mode = "positive",
  mzabs.error = 0.01, ppm.error = 10, ads = NULL, nls = NULL,
  adwts = NULL, nlwts = NULL, plot.findmain = TRUE, writeMat = TRUE)

Arguments

ramclustObj	ramclustR object to annotate.
cmpd	integer: vector defining compound numbers to annotated. if NULL (default), all compounds
mode	character: "positive" or "negative"
mzabs.error	numeric: absolute mass deviation allowd
ppm.error	numeric: ppm mass error added to mzabs.error
ads	character: vector of allowed adducts, i.e. c("[M+H]+"). if NULL, default values of H+, Na+, K+, and NH4+, as monomer, dimer, and trimer, are assigned.
nls	character: vector of allowed neutral losses, i.e. c("[M+H-H2O]+"). if NULL, an extensive list derived from CAMERA's will be used.
adwts	numeric: vector of weights for adducts. length should match that of 'ads', else first value will be repeated. if NULL (default), value of 1 is assigned to all. Only used for ramclustR scoring of M.
nlwts	numeric: vector of weights for neutral losses. length should match that of 'nls', else first value will be repeated. if NULL (default), value of 0.1 is assigned to all. Only used for ramclustR scoring of M.
plot.findmain	logical: should pdf polts be generated for evaluation?
writeMat	logical: should indidual .mat files (for MSFinder) be generated in a 'mat' subdirectory in the 'spectra' folder? default = TRUE.

Details

a partially annotated ramclustR object. base structure is that of a standard R heirarchical clustering output, with additional slots described in ramclustR documentation (?ramclustR). New slots added after using the interpretMSSpectrum functionality include those described below. .mat files written in new directory 'spectra/mat' in working directory

Value

$M: The inferred molecular weight of the compound giving rise to the each spectrum

$M.ppm: The ppm error of all the MS signals annotated, high error values should be considered 'red flags'

$M.ann: The annotated spectrum supporting the intepretation of M

$use.findmain: Logical vector indicating whether findmain scoring (TRUE) or ramclustR scoring (FALSE) was used to support inference of M. By default, findmain scoring is used. When ramclustR scoring differs from findmain scoring, the scoring metric which predicts higher M is selected.

$M.ramclustr: M selected using ramclustR scoring

$M.ppm.ramclustr: ppm error of M selected using ramclustR scoring

$M.ann.ramclustr: annotated spectrum supporing M using ramclustR scoring

$M.findmain: M selected using findmain scoring

$M.ppm.findmain: ppm error of M selected using findmain scoring

$M.ann.findmain: annotated spectrum supporing M using findmain scoring

Author(s)

Corey Broeckling

References

Jaeger C, M<c3><a9>ret M, Schmitt CA, Lisec J. Compound annotation in liquid chromatography/high-resolution mass spectrometry based metabolomics: robust adduct ion determination as a prerequisite to structure prediction in electrospray ionization mass spectra. Rapid Commun Mass Spectrom. 2017 Aug 15;31(15):1261-1266. doi: 10.1002/rcm.7905. PubMed PMID: 28499062.

Broeckling CD, Afsar FA, Neumann S, Ben-Hur A, Prenni JE. RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Anal Chem. 2014 Jul 15;86(14):6812-7. doi: 10.1021/ac501530d. Epub 2014 Jun 26. PubMed PMID: 24927477.

Broeckling CD, Ganna A, Layer M, Brown K, Sutton B, Ingelsson E, Peers G, Prenni JE. Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction. Anal Chem. 2016 Sep 20;88(18):9226-34. doi: 10.1021/acs.analchem.6b02479. Epub 2016 Sep 8. PubMed PMID: 7560453.

sneumann/RAMClustR documentation built on May 30, 2019, 5:05 a.m.