aggregateSpectra: Aggregate analyzed spectra

In sneumann/RMassBank: Workflow to process tandem MS files and build MassBank records

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)

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.

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.

Author(s)

Michael Stravs

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)

sneumann/RMassBank documentation built on Oct. 20, 2020, 3:19 p.m.