Description Usage Arguments Value Examples
General
Average and filter fragmentation spectra for each XCMS feature within and across MS data files (ignoring intra and inter relationships).
The averaging is performed using hierarchical clustering of the m/z values of each peaks, where m/z values within a set ppm tolerance will be clustered. The clustered peaks are then averaged (or summed).
The fragmentation can be filtered on the averaged spectra (with the arguments snr, rsd, minfrac, ra)
Example LC-MS/MS processing workflow
Purity assessments
(mzML files) -> purityA -> (pa)
XCMS processing
(mzML files) -> xcms.xcmsSet -> xcms.merge -> xcms.group -> xcms.retcor -> xcms.group -> (xset)
Fragmentation processing
(xset, pa) -> frag4feature -> filterFragSpectra -> averageAllFragSpectra -> createDatabase -> spectralMatching -> (sqlite spectral database)
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## S4 method for signature 'purityA'
averageAllFragSpectra(
pa,
minfrac = 0.5,
minnum = 1,
ppm = 5,
snr = 0,
ra = 0,
av = "median",
sumi = TRUE,
rmp = FALSE,
cores = 1
)
|
pa |
object; purityA object |
minfrac |
numeric;minimum ratio of the peak fraction (peak count / total peaks) across all (ignoring intra and inter relationships) |
minnum |
numeric; minimum number of times peak is present across all fragmentation spectra (ignoring intra and inter relationships) |
ppm |
numeric; ppm threshold to average across all scans (ignoring intra and inter relationships) |
snr |
numeric; minimum signal-to-noise of the peak across all (ignoring intra and inter relationships) |
ra |
numeric; minimum relative abundance of the peak fraction across all (ignoring intra and inter relationships) |
av |
character; type of averaging to use (median or mean) |
sumi |
boolean; TRUE if the intensity for each peak is summed across averaged spectra |
rmp |
boolean; TRUE if peaks are to be removed that do not meet the threshold criteria. Otherwise they will just be flagged |
cores |
numeric; Number of cores for multiprocessing |
Returns a purityA object (pa) with the following slots now with data
pa@av_spectra: the average spectra is recorded here stored as a list. E.g. pa@av_spectra$1
$av_all would give the average spectra for grouped feature 1.
pa@av_all_params: The parameters used are recorded here
Each spectra in the av_spectra list contains the following columns:
cl: id of clustered (averaged) peak
mz: average m/z
i: average intensity
snr: average signal to noise ratio
rsd: relative standard deviation
count: number of clustered peaks
total: total number of potential scans to be used for averaging
inPurity: average precursor ion purity
ra: average relative abundance
frac: the fraction of clustered peaks (e.g. the count/total)
snr_pass_flag: TRUE if snr threshold criteria met
minfrac_pass_flag: TRUE if minfrac threshold criteria
ra_pass_flag: TRUE if ra threshold criteria met
pass_flag: TRUE if all threshold criteria met
1 2 3 4 5 6 7 8 9 10 11 12 13 | #msmsPths <- list.files(system.file("extdata", "lcms", "mzML",
#package="msPurityData"), full.names = TRUE, pattern = "MSMS")
#xset <- xcms::xcmsSet(msmsPths, nSlaves = 1)
#xset <- xcms::group(xset)
#xset <- xcms::retcor(xset)
#xset <- xcms::group(xset)
#pa <- purityA(msmsPths, interpol = "linear")
#pa <- frag4feature(pa, xset)
#pa <- filterFragSpectra(pa)
pa <- readRDS(system.file("extdata", "tests", "purityA",
"3_filterFragSpectra_pa.rds", package="msPurity"))
pa <- averageAllFragSpectra(pa)
|
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