RMassBank (version 2.0.0)

aggregateSpectra: Aggregate analyzed spectra

Description

Groups an array of analyzed spectra and creates aggregated peak tables

Usage

aggregateSpectra(spec,  addIncomplete=FALSE)

Arguments

spec

The RmbSpectraSetList of spectra sets (RmbSpectraSet objects) to aggregate

addIncomplete

Whether or not the peaks from incomplete files (files for which less than the maximal number of spectra are present)

Value

A summary data.frame with all peaks (possibly multiple rows for one m/z value from a spectrum, see below) with columns:

mzFound, intensity

Mass and intensity of the peak

good

if the peak passes filter criteria

mzCalc, formula, dbe, dppm

calculated mass, formula, dbe and ppm deviation of the assigned formula

formulaCount, dppmBest

Number of matched formulae for this m/z value, and ppm deviation of the best match

scan, cpdID, parentScan

Scan number of the child and parent spectrum in the raw file, also the compound ID to which the peak belongs

dppmRc

ppm deviation recalculated from the aggregation function

index

Aggregate-table peak index, so the table can be subsetted, edited and results reinserted back into this table easily

Further columns are later added by workflow steps 6 (electronic noise culler), 7 and 8.

Details

addIncomplete is relevant for recalibration. For recalibration, we want to use only high-confidence peaks, therefore we set addIncomplete to FALSE. When we want to generate a peak list for actually generating MassBank records, we want to include all peaks into the peak tables.

See Also

msmsWorkflow, analyzeMsMs

Examples

## As used in the workflow:
## Not run: %
# 	w@spectra <- lapply(w@spectra, function(spec)
# 		analyzeMsMs(spec, mode="pH", detail=TRUE, run="recalibrated", cut=0, cut_ratio=0 ) )
# 	w@aggregate <- aggregateSpectra(w@spectra)
# ## End(Not run)