averageSpectra,purityD-method | R Documentation |
Uses a purityD object with references to multiple MS files. For each file: Averages multiple scans together, see averageSpectraSingle for more information
## S4 method for signature 'purityD' averageSpectra( Object, rtscn = "all", scanRange = NA, timeRange = NA, clustType = "hc", ppm = 1.5, snthr = 3, av = "median", missingV = "zero", minfrac = 0.6667, normTIC = FALSE, snMeth = "median" )
Object |
object; purityD object |
rtscn |
character; Whether it is scans or retention time to be filtered. Use "all" if all scans to be used. ['rt', 'scns', 'all'] |
scanRange |
vector; Scan range (if rtscn='scns') e.g. c(40, 69) |
timeRange |
vector; Time range (if rtscn='rt) e.g. c(10.3, 400.8) (only if using mzML file) |
clustType |
character; Type of clustering used either Hierarchical or just simple 1D grouping ['hc', 'simple'] |
ppm |
numeric; The ppm error to cluster mz together |
snthr |
numeric; Signal to noise ratio threshold |
av |
character; What type of averaging to do between peaks |
missingV |
character; What to do with missing values (zero or ignore) |
minfrac |
numeric; Min fraction of scans with a grouped peak to be an accepted averaged peak |
normTIC |
boolean; If TRUE then RSD calculation will use the normalised intensity (intensity divided by TIC) if FALSE will use standard intensity |
snMeth |
character; Type of snMethod to use ['mean', 'median', 'precalc']. Precalc only applicable when using the csvFile parameter as TRUE |
purityD object with averaged spectra
averageSpectraSingle
datapth <- system.file("extdata", "dims", "mzML", package="msPurityData") inDF <- Getfiles(datapth, pattern=".mzML", check = FALSE, cStrt = FALSE) ppDIMS <- purityD(fileList=inDF, cores=1, mzML=TRUE) ppDIMS <- averageSpectra(ppDIMS)
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