The OnDiskMSnExp Class for MS Data And Meta-Data
OnDiskMSnExp-class.RdLike the MSnExp class, the OnDiskMSnExp class
encapsulates data and meta-data for mass spectrometry
experiments, but does, in contrast to the former, not keep the
spectrum data in memory, but fetches the M/Z and intensity values on
demand from the raw files. This results in some instances to a
reduced performance, has however the advantage of a much smaller
memory footprint.
Details
The OnDiskMSnExp object stores many spectrum related
information into the featureData, thus, some calls, like
rtime to retrieve the retention time of the individual scans
does not require the raw data to be read. Only M/Z and intensity
values are loaded on-the-fly from the original files. Extraction of
values for individual scans is, for mzML files, very fast. Extraction
of the full data (all spectra) are performed in a per-file parallel
processing strategy.
Data manipulations related to spectras' M/Z or intensity values
(e.g. removePeaks or clean) are (for
OnDiskMSnExp objects) not applied immediately, but are stored
for later execution into the spectraProcessingQueue. The
manipulations are performed on-the-fly upon data retrieval.
Other manipulations, like removal of individual spectra are applied
directly, since the corresponding data is available in the object's
featureData slot.
Objects from the Class
Objects can be created by calls of the form
new("OnDiskMSnExp",...). However, it is preferred to use the
readMSData function with argument backend="disk"
that will read raw mass spectrometry data to generate a valid
"OnDiskMSnExp" instance.
Slots
backend:Character string specifying the used backend.
spectraProcessingQueue:listofProcessingStepobjects defining the functions to be applied on-the-fly to the spectra data (M/Z and intensity duplets).assayData:Object of class
"environment"that is however empty, as no spectrum data is stored. Slot is inherited from"pSet".phenoData:Object of class
"AnnotatedDataFrame"containing experimenter-supplied variables describing sample (i.e the individual tags for an labelled MS experiment) SeephenoDatafor more details. Slot is inherited from"pSet".featureData:Object of class
"AnnotatedDataFrame"containing variables describing features (spectra in our case). SeefeatureDatafor more details. Slot is inherited from"pSet".experimentData:Object of class
"MIAPE", containing details of experimental methods. SeeexperimentDatafor more details. Slot is inherited from"pSet".protocolData:Object of class
"AnnotatedDataFrame"containing equipment-generated variables (inherited from"eSet"). SeeprotocolDatafor more details. Slot is inherited from"pSet".processingData:Object of class
"MSnProcess"that records all processing. Slot is inherited from"pSet"..__classVersion__:Object of class
"Versions"describing the versions of R, the Biobase package,"pSet"andMSnExpof the current instance. Slot is inherited from"pSet". Intended for developer use and debugging (inherited from"eSet").
Extends
Class "MSnExp", directly.
Class "pSet", by class "MSnExp", distance 3.
Class "VersionedBiobase", by class "pSet", distance 4.
Class "Versioned", by class "pSet", distance 5.
Getter/setter methods
(in alphabetical order)
See also methods for MSnExp or
pSet objects.
- [
object[i]:subset theOnDiskMSnExpby spectra.ican be anumericorlogicalvector specifying to which spectra the data set should be reduced (withibeing the index of the spectrum in the object'sfeatureData).The method returns a
OnDiskMSnExpobject with the data sub-set.- [[
object[[i]]: extract s single spectrum from theOnDiskMSnExpobjectobject. Argumentican be either numeric or character specifying the index or the name of the spectrum in the object (i.e. in thefeatureData). The relevant information will be extracted from the corresponding raw data file.The method returns a
Spectrum1object.- acquisitionNum
acquisitionNum(signature(object="OnDiskMSnExp")): get the acquisition number of each spectrum in each individual file. The relevant information is extracted from the object'sfeatureDataslot.Returns a numeric vector with names corresponding to the spectrum names.
- assayData
assayData(signature(object = "OnDiskMSnExp")): Extract the full data, i.e. read all spectra from the original files, apply all processing steps from thespectraProcessingQueueslot and return the data. Due to the required processing time accessing the full data should be avoided wherever possible.Returns an
environment.- centroided,centroided<-
centroided(signature(object="OnDiskMSnExp", msLevel, = "numeric")): whether individual spectra are centroided or uncentroided. The relevant information is extracted from the object'sfeatureDataslot. Returns a logical vector with names corresponding to the spectrum names. Usecentroided(object) <- valueto update the information, with value being a logical vector of length equal to the number of spectra in the experiment.isCentroided(object, k = 0.025, qtl = 0.9, verbose = TRUE)A heuristic assessing if the spectra in the
objectare in profile or centroided mode. The function takes theqtlth quantile top peaks, then calculates the difference between adjacent M/Z value and returnsTRUEif the first quartile is greater thank. (SeeMSnbase:::.isCentroidedfor the code.) Ifverbose(default), a table indicating mode for all MS levels is printed.The function has been tuned to work for MS1 and MS2 spectra and data centroided using different peak picking algorithms, but false positives can occur. See https://github.com/lgatto/MSnbase/issues/131 for details. For whole experiments, where all MS1 and MS2 spectra are expected to be in the same, albeit possibly different modes, it is advised to assign the majority result for MS1 and MS2 spectra, rather than results for individual spectra.
See also
isCentroidedFromFilethat accessed the mode directly from the raw data file.- fromFile
fromFile(signature(object = "OnDiskMSnExp")): get the index of the file (infileNames(object)) from which the spectra were read. The relevant information is extracted from the object'sfeatureDataslot.Returns a numeric vector with names corresponding to the spectrum names.
- intensity
intensity(signature(object="OnDiskMSnExp")): return the intensities from each spectrum in the data set. Intensities are first read from the raw files followed by an optional processing (depending on the processing steps defined in thespectraProcessingQueue). To reduce the amount of required memory, this is performed on a per-file basis. TheBPPARAMargument allows to specify how and if parallel processing should be used. Information from individual files will be processed in parallel (one process per original file).The method returns a
listof numeric intensity values. Each list element represents the intensities from one spectrum.- ionCount
ionCount(signature(object="OnDiskMSnExp", BPPARAM=bpparam())): extract the ion count (i.e. sum of intensity values) for each spectrum in the data set. The relevant data has to be extracted from the raw files (with eventually applying processing steps). TheBPPARAMargument can be used to define how and if parallel processing should be used. Information from individual files will be processed in parallel (one process per original file).Returns a numeric vector with names corresponding to the spectrum names.
- isolationWindowLowerMz
isolationWindowLowerMz(object = "OnDiskMSnExp"): return the lower m/z boundary for the isolation window.Returns a numeric vector of length equal to the number of spectra with the lower m/z value of the isolation window or
NAif not specified in the original file.- isolationWindowUpperMz
isolationWindowUpperMz(object = "OnDiskMSnExp"): return the upper m/z boundary for the isolation window.Returns a numeric vector of length equal to the number of spectra with the upper m/z value of the isolation window or
NAif not specified in the original file.- length
length(signature(object="OnDiskMSnExp")): Returns the number of spectra of the current experiment.- msLevel
msLevel(signature(object = "OnDiskMSnExp")): extract the MS level from the spectra. The relevant information is extracted from the object'sfeatureDataslot.Returns a numeric vector with names corresponding to the spectrum names.
- mz
mz(signature(object="OnDiskMSnExp")): return the M/Z values from each spectrum in the data set. M/Z values are first read from the raw files followed by an optional processing (depending on the processing steps defined in thespectraProcessingQueue). To reduce the amount of required memory, this is performed on a per-file basis. TheBPPARAMargument allows to specify how and if parallel processing should be used. Information from individual files will be processed in parallel (one process per original file).The method returns a
listof numeric M/Z values. Each list element represents the values from one spectrum.- peaksCount
peaksCount(signature(object="OnDiskMSnExp", scans="numeric"), BPPARAM=bpparam()): extrac the peaks count from each spectrum in the object. Depending on the eventually presentProcessingStepobjects in thespectraProcessingQueueraw data will be loaded to calculate the peaks count. If no steps are present, the data is extracted from thefeatureData. Optional argumentscansallows to specify the index of specific spectra from which the count should be returned. TheBPPARAMargument can be used to define how and if parallel processing should be used. Information from individual files will be processed in parallel (one process per original file).Returns a numeric vector with names corresponding to the spectrum names.
- polarity
polarity(signature(object="OnDiskMSnExp")): returns a numeric vector with the polarity of the individual spectra in the data set. The relevant information is extracted from thefeatureData.- rtime
rtime(signature(object="OnDiskMSnExp")): extrac the retention time of the individual spectra in the data set (from thefeatureData).Returns a numeric vector with names corresponding to the spectrum names.
- scanIndex
scanIndex(signature(object="OnDiskMSnExp")): get the spectra scan indices within the respective file. The relevant information is extracted from the object'sfeatureDataslot. Returns a numeric vector of indices with names corresponding to the spectrum names.- smoothed,smoothed<-
smoothed(signature(object="OnDiskMSnExp", msLevel. = "numeric")): whether individual spectra are smoothed or unsmoothed. The relevant information is extracted from the object'sfeatureDataslot. Returns a logical vector with names corresponding to the spectrum names. Usesmoothed(object) <- valueto update the information, with value being a logical vector of length equal to the number of spectra in the experiment.- spectra
spectra(signature(object="OnDiskMSnExp"), BPPARAM=bpparam()): extract spectrum data from the individual files. This causes the spectrum data to be read from the original raw files. After that all processing steps defined in thespectraProcessingQueueare applied to it. The results are then returned as alistofSpectrum1objects.The
BPPARAMargument can be used to define how and if parallel processing should be used. Information from individual files will be processed in parallel (one process per file). Note: extraction of selected spectra results in a considerable processing speed and should thus be preferred over whole data extraction.Returns a
listofSpectrum1objects with names corresponding to the spectrum names.- tic
tic(signature(object="OnDiskMSnExp"), initial = TRUE, BPPARAM = bpparam()): get the total ion current (TIC) of each spectrum in the data set. Ifinitial = TRUE, the information is extracted from the object'sfeatureDataand represents the tic provided in the header of the original raw data files. Forinitial = FALSE, the TIC is calculated from the actual intensity values in each spectrum after applying all data manipulation methods (if any).See also https://github.com/lgatto/MSnbase/issues/332 for more details.
BPPARAMparameter: seespectramethod above.Returns a numeric vector with names corresponding to the spectrum names.
- bpi
bpi(signature(object="OnDiskMSnExp"), initial = TRUE, BPPARAM = bpparam()): get the base peak intensity (BPI), i.e. the maximum intensity from each spectrum in the data set. Ifinitial = TRUE, the information is extracted from the object'sfeatureDataand represents the bpi provided in the header of the original raw data files. Forinitial = FALSE, the BPI is calculated from the actual intensity values in each spectrum after applying all eventual data manipulation methods.See also https://github.com/lgatto/MSnbase/issues/332 for more details.
BPPARAMparameter: seespectramethod above.Returns a numeric vector with names corresponding to the spectrum names.
- featureNames
tic(signature(object="OnDiskMSnExp")): return acharacterof lengthlength(object)containing the feature names. A replacement method is also available.- spectrapply
spectrapply(signature(object = "OnDiskMSnExp"), FUN = NULL, BPPARAM = bpparam(), ...): applies the functionFUNto each spectrum passing additional parameters in...to that function and return its results. ForFUN = NULLit returns the list of spectra (same as a call tospectra). ParameterBPPARAMallows to specify how and if parallel processing should be enabled.Returns a list with the result for each of spectrum.
Data manipulation methods
(in alphabetical order)
See also methods for MSnExp or
pSet objects. In contrast to the same-named
methods for pSet or MSnExp
classes, the actual data manipulation is not performed immediately,
but only on-demand, e.g. when intensity or M/Z values are loaded.
- clean
clean(signature(object="OnDiskMSnExp"), all=TRUE, verbose=TRUE): add an clean processing step to the lazy processing queue of theOnDiskMSnExpobject. Thecleancommand will only be executed when spectra information (including M/Z and intensity values) is requested from theOnDiskMSnExpobject. Optional arguments to the methods areall=TRUEandverbose=TRUE.The method returns an
OnDiskMSnExpobject.For more details see documentation of the
cleanmethod.- normalize
normalize(signature(object="OnDiskMSnExp"), method=c("max", "sum"), ...): add anormalizeprocessing step to the lazy processing queue of the returnedOnDiskMSnExpobject.The method returns an
OnDiskMSnExpobject.For more details see documentation of the
normalizemethod.- removePeaks
removePeaks(signature(object="OnDiskMSnExp"), t="min", verbose=TRUE): add aremovePeaksprocessing step to the lazy processing queue of the returnedOnDiskMSnExpobject.The method returns an
OnDiskMSnExpobject.For more details see documentation of the
removePeaksmethod.- trimMz
trimMz(signature(object="OnDiskMSnExp", mzlim="numeric"),...): add atrimMzprocessing step to the lazy processing queue of the returnedOnDiskMSnExpobject.The method returns an
OnDiskMSnExpobject.For more details see documentation of the
trimMzmethod.
Other methods and functions
- validateOnDiskMSnExp
validateOnDiskMSnExp(signature(object = "OnDiskMSnExp")): validates anOnDiskMSnExpobject and all of its spectra. In addition to the standardvalidObjectmethod, this method reads also all spectra from the original files, applies eventual processing steps and evaluates their validity.as(from, "MSnExp")Converts the
OnDiskMSnExpobjectfrom, to an in-memoryMSnExp. Also available as an S3 methodas.MSnExp().
Examples
## Get some example mzML files
library(msdata)
mzfiles <- c(system.file("microtofq/MM14.mzML", package="msdata"),
system.file("microtofq/MM8.mzML", package="msdata"))
## Read the data as an OnDiskMSnExp
odmse <- readMSData(mzfiles, msLevel=1, centroided = TRUE)
## Get the length of data, i.e. the total number of spectra.
length(odmse)
#> [1] 310
## Get the MS level
head(msLevel(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 1 1 1 1 1
## Get the featureData, use fData to return as a data.frame
head(fData(odmse))
#> spectrum
#> F1.S001 1
#> F1.S002 2
#> F1.S003 3
#> F1.S004 4
#> F1.S005 5
#> F1.S006 6
## Get to know from which file the spectra are
head(fromFile(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 1 1 1 1 1
## And the file names:
fileNames(odmse)
#> [1] "/__w/_temp/Library/msdata/microtofq/MM14.mzML"
#> [2] "/__w/_temp/Library/msdata/microtofq/MM8.mzML"
## Scan index and acquisitionNum
head(scanIndex(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 2 3 4 5 6
head(acquisitionNum(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 2 3 4 5 6
## Extract the spectra; the data is retrieved from the raw files.
head(spectra(odmse))
#> $F1.S001
#> Object of class "Spectrum1"
#> Retention time: 4:30
#> MSn level: 1
#> Total ion count: 1378
#> Polarity: 1
#>
#> $F1.S002
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1356
#> Polarity: 1
#>
#> $F1.S003
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1404
#> Polarity: 1
#>
#> $F1.S004
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1496
#> Polarity: 1
#>
#> $F1.S005
#> Object of class "Spectrum1"
#> Retention time: 4:32
#> MSn level: 1
#> Total ion count: 1525
#> Polarity: 1
#>
#> $F1.S006
#> Object of class "Spectrum1"
#> Retention time: 4:32
#> MSn level: 1
#> Total ion count: 1498
#> Polarity: 1
#>
## Extracting individual spectra or a subset is much faster.
spectra(odmse[1:50])
#> $F1.S001
#> Object of class "Spectrum1"
#> Retention time: 4:30
#> MSn level: 1
#> Total ion count: 1378
#> Polarity: 1
#>
#> $F1.S002
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1356
#> Polarity: 1
#>
#> $F1.S003
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1404
#> Polarity: 1
#>
#> $F1.S004
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 1496
#> Polarity: 1
#>
#> $F1.S005
#> Object of class "Spectrum1"
#> Retention time: 4:32
#> MSn level: 1
#> Total ion count: 1525
#> Polarity: 1
#>
#> $F1.S006
#> Object of class "Spectrum1"
#> Retention time: 4:32
#> MSn level: 1
#> Total ion count: 1498
#> Polarity: 1
#>
#> $F1.S007
#> Object of class "Spectrum1"
#> Retention time: 4:32
#> MSn level: 1
#> Total ion count: 1484
#> Polarity: 1
#>
#> $F1.S008
#> Object of class "Spectrum1"
#> Retention time: 4:33
#> MSn level: 1
#> Total ion count: 1532
#> Polarity: 1
#>
#> $F1.S009
#> Object of class "Spectrum1"
#> Retention time: 4:33
#> MSn level: 1
#> Total ion count: 1532
#> Polarity: 1
#>
#> $F1.S010
#> Object of class "Spectrum1"
#> Retention time: 4:33
#> MSn level: 1
#> Total ion count: 1513
#> Polarity: 1
#>
#> $F1.S011
#> Object of class "Spectrum1"
#> Retention time: 4:34
#> MSn level: 1
#> Total ion count: 1563
#> Polarity: 1
#>
#> $F1.S012
#> Object of class "Spectrum1"
#> Retention time: 4:34
#> MSn level: 1
#> Total ion count: 1522
#> Polarity: 1
#>
#> $F1.S013
#> Object of class "Spectrum1"
#> Retention time: 4:34
#> MSn level: 1
#> Total ion count: 1571
#> Polarity: 1
#>
#> $F1.S014
#> Object of class "Spectrum1"
#> Retention time: 4:35
#> MSn level: 1
#> Total ion count: 1553
#> Polarity: 1
#>
#> $F1.S015
#> Object of class "Spectrum1"
#> Retention time: 4:35
#> MSn level: 1
#> Total ion count: 1606
#> Polarity: 1
#>
#> $F1.S016
#> Object of class "Spectrum1"
#> Retention time: 4:35
#> MSn level: 1
#> Total ion count: 1583
#> Polarity: 1
#>
#> $F1.S017
#> Object of class "Spectrum1"
#> Retention time: 4:36
#> MSn level: 1
#> Total ion count: 1567
#> Polarity: 1
#>
#> $F1.S018
#> Object of class "Spectrum1"
#> Retention time: 4:36
#> MSn level: 1
#> Total ion count: 1662
#> Polarity: 1
#>
#> $F1.S019
#> Object of class "Spectrum1"
#> Retention time: 4:36
#> MSn level: 1
#> Total ion count: 1628
#> Polarity: 1
#>
#> $F1.S020
#> Object of class "Spectrum1"
#> Retention time: 4:37
#> MSn level: 1
#> Total ion count: 1604
#> Polarity: 1
#>
#> $F1.S021
#> Object of class "Spectrum1"
#> Retention time: 4:37
#> MSn level: 1
#> Total ion count: 1647
#> Polarity: 1
#>
#> $F1.S022
#> Object of class "Spectrum1"
#> Retention time: 4:37
#> MSn level: 1
#> Total ion count: 1594
#> Polarity: 1
#>
#> $F1.S023
#> Object of class "Spectrum1"
#> Retention time: 4:38
#> MSn level: 1
#> Total ion count: 1643
#> Polarity: 1
#>
#> $F1.S024
#> Object of class "Spectrum1"
#> Retention time: 4:38
#> MSn level: 1
#> Total ion count: 1673
#> Polarity: 1
#>
#> $F1.S025
#> Object of class "Spectrum1"
#> Retention time: 4:38
#> MSn level: 1
#> Total ion count: 1695
#> Polarity: 1
#>
#> $F1.S026
#> Object of class "Spectrum1"
#> Retention time: 4:39
#> MSn level: 1
#> Total ion count: 1595
#> Polarity: 1
#>
#> $F1.S027
#> Object of class "Spectrum1"
#> Retention time: 4:39
#> MSn level: 1
#> Total ion count: 1592
#> Polarity: 1
#>
#> $F1.S028
#> Object of class "Spectrum1"
#> Retention time: 4:39
#> MSn level: 1
#> Total ion count: 1614
#> Polarity: 1
#>
#> $F1.S029
#> Object of class "Spectrum1"
#> Retention time: 4:40
#> MSn level: 1
#> Total ion count: 1558
#> Polarity: 1
#>
#> $F1.S030
#> Object of class "Spectrum1"
#> Retention time: 4:40
#> MSn level: 1
#> Total ion count: 1539
#> Polarity: 1
#>
#> $F1.S031
#> Object of class "Spectrum1"
#> Retention time: 4:40
#> MSn level: 1
#> Total ion count: 1532
#> Polarity: 1
#>
#> $F1.S032
#> Object of class "Spectrum1"
#> Retention time: 4:41
#> MSn level: 1
#> Total ion count: 1546
#> Polarity: 1
#>
#> $F1.S033
#> Object of class "Spectrum1"
#> Retention time: 4:41
#> MSn level: 1
#> Total ion count: 1506
#> Polarity: 1
#>
#> $F1.S034
#> Object of class "Spectrum1"
#> Retention time: 4:41
#> MSn level: 1
#> Total ion count: 1428
#> Polarity: 1
#>
#> $F1.S035
#> Object of class "Spectrum1"
#> Retention time: 4:42
#> MSn level: 1
#> Total ion count: 1448
#> Polarity: 1
#>
#> $F1.S036
#> Object of class "Spectrum1"
#> Retention time: 4:42
#> MSn level: 1
#> Total ion count: 1431
#> Polarity: 1
#>
#> $F1.S037
#> Object of class "Spectrum1"
#> Retention time: 4:42
#> MSn level: 1
#> Total ion count: 1393
#> Polarity: 1
#>
#> $F1.S038
#> Object of class "Spectrum1"
#> Retention time: 4:43
#> MSn level: 1
#> Total ion count: 1409
#> Polarity: 1
#>
#> $F1.S039
#> Object of class "Spectrum1"
#> Retention time: 4:43
#> MSn level: 1
#> Total ion count: 1410
#> Polarity: 1
#>
#> $F1.S040
#> Object of class "Spectrum1"
#> Retention time: 4:43
#> MSn level: 1
#> Total ion count: 1342
#> Polarity: 1
#>
#> $F1.S041
#> Object of class "Spectrum1"
#> Retention time: 4:44
#> MSn level: 1
#> Total ion count: 1366
#> Polarity: 1
#>
#> $F1.S042
#> Object of class "Spectrum1"
#> Retention time: 4:44
#> MSn level: 1
#> Total ion count: 1351
#> Polarity: 1
#>
#> $F1.S043
#> Object of class "Spectrum1"
#> Retention time: 4:44
#> MSn level: 1
#> Total ion count: 1367
#> Polarity: 1
#>
#> $F1.S044
#> Object of class "Spectrum1"
#> Retention time: 4:45
#> MSn level: 1
#> Total ion count: 1342
#> Polarity: 1
#>
#> $F1.S045
#> Object of class "Spectrum1"
#> Retention time: 4:45
#> MSn level: 1
#> Total ion count: 1365
#> Polarity: 1
#>
#> $F1.S046
#> Object of class "Spectrum1"
#> Retention time: 4:45
#> MSn level: 1
#> Total ion count: 1379
#> Polarity: 1
#>
#> $F1.S047
#> Object of class "Spectrum1"
#> Retention time: 4:46
#> MSn level: 1
#> Total ion count: 1325
#> Polarity: 1
#>
#> $F1.S048
#> Object of class "Spectrum1"
#> Retention time: 4:46
#> MSn level: 1
#> Total ion count: 1349
#> Polarity: 1
#>
#> $F1.S049
#> Object of class "Spectrum1"
#> Retention time: 4:46
#> MSn level: 1
#> Total ion count: 1383
#> Polarity: 1
#>
#> $F1.S050
#> Object of class "Spectrum1"
#> Retention time: 4:47
#> MSn level: 1
#> Total ion count: 1342
#> Polarity: 1
#>
## Alternatively, we could also subset the whole object by spectra and/or samples:
subs <- odmse[rtime(odmse) >= 2 & rtime(odmse) <= 20, ]
fileNames(subs)
#> [1] "/__w/_temp/Library/msdata/microtofq/MM8.mzML"
rtime(subs)
#> F2.S006 F2.S007 F2.S008 F2.S009 F2.S010 F2.S011 F2.S012 F2.S013
#> 2.169000 2.506002 2.842998 3.178998 3.516000 3.852000 4.188000 4.525002
#> F2.S014 F2.S015 F2.S016 F2.S017 F2.S018 F2.S019 F2.S020 F2.S021
#> 4.861002 5.197998 5.533998 5.871000 6.207000 6.544020 6.880020 7.216980
#> F2.S022 F2.S023 F2.S024 F2.S025 F2.S026 F2.S027 F2.S028 F2.S029
#> 7.554000 7.891020 8.227020 8.563980 8.899980 9.237000 9.573000 9.910020
#> F2.S030 F2.S031 F2.S032 F2.S033 F2.S034 F2.S035 F2.S036 F2.S037
#> 10.246020 10.582020 10.918980 11.254980 11.592000 11.928000 12.265020 12.601020
#> F2.S038 F2.S039 F2.S040 F2.S041 F2.S042 F2.S043 F2.S044 F2.S045
#> 12.937020 13.273980 13.609980 13.947000 14.283000 14.620020 14.956020 15.292020
#> F2.S046 F2.S047 F2.S048 F2.S049 F2.S050 F2.S051 F2.S052 F2.S053
#> 15.628980 15.964980 16.302000 16.638000 16.975020 17.311020 17.649000 17.986020
#> F2.S054 F2.S055 F2.S056 F2.S057 F2.S058
#> 18.322980 18.660000 18.996000 19.333020 19.669020
## Extract intensities and M/Z values per spectrum; the methods return a list,
## each element representing the values for one spectrum.
ints <- intensity(odmse)
mzs <- mz(odmse)
## Return a data.frame with mz and intensity pairs for each spectrum from the
## object
res <- spectrapply(odmse, FUN = as, Class = "data.frame")
## Calling removePeaks, i.e. setting intensity values below a certain threshold to 0.
## Unlike the name suggests, this is not actually removing peaks. Such peaks with a 0
## intensity are then removed by the "clean" step.
## Also, the manipulations are not applied directly, but put into the "lazy"
## processing queue.
odmse <- removePeaks(odmse, t=10000)
odmse <- clean(odmse)
## The processing steps are only applied when actual raw data is extracted.
spectra(odmse[1:2])
#> $F1.S001
#> Object of class "Spectrum1"
#> Retention time: 4:30
#> MSn level: 1
#> Total ion count: 0
#> Polarity: 1
#>
#> $F1.S002
#> Object of class "Spectrum1"
#> Retention time: 4:31
#> MSn level: 1
#> Total ion count: 0
#> Polarity: 1
#>
## Get the polarity of the spectra.
head(polarity(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 1 1 1 1 1
## Get the retention time of all spectra
head(rtime(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 270.334 270.671 271.007 271.343 271.680 272.016
## Get the intensities after removePeaks and clean
intsAfter <- intensity(odmse)
head(lengths(ints))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1378 1356 1404 1496 1525 1498
head(lengths(intsAfter))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 0 0 0 3 6 9
## The same for the M/Z values
mzsAfter <- intensity(odmse)
head(lengths(mzs))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1378 1356 1404 1496 1525 1498
head(lengths(mzsAfter))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 0 0 0 3 6 9
## Centroided or profile mode
f <- msdata::proteomics(full.names = TRUE,
pattern = "MS3TMT11.mzML")
odmse <- readMSData(f, mode = "onDisk")
validObject(odmse)
#> [1] TRUE
odmse[[1]]
#> Object of class "Spectrum1"
#> Retention time: 45:27
#> MSn level: 1
#> Total ion count: 10768
#> Polarity: 1
table(isCentroidedFromFile(odmse), msLevel(odmse))
#>
#> 1 2 3
#> FALSE 30 0 0
#> TRUE 0 482 482
## centroided status could be set manually
centroided(odmse, msLevel = 1) <- FALSE
centroided(odmse, msLevel = 2) <- TRUE
centroided(odmse, msLevel = 3) <- TRUE
## or when reading the data
odmse2 <- readMSData(f, centroided = c(FALSE, TRUE, TRUE),
mode = "onDisk")
table(centroided(odmse), msLevel(odmse))
#>
#> 1 2 3
#> FALSE 30 0 0
#> TRUE 0 482 482
## Filtering precursor scans
head(acquisitionNum(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 21945 21946 21947 21948 21949 21950
head(msLevel(odmse))
#> F1.S001 F1.S002 F1.S003 F1.S004 F1.S005 F1.S006
#> 1 2 2 3 2 2
## Extract all spectra stemming from the first MS1 spectrum
(from1 <- filterPrecursorScan(odmse, 21945))
#> MSn experiment data ("OnDiskMSnExp")
#> Object size in memory: 0.05 Mb
#> - - - Spectra data - - -
#> MS level(s): 1 2 3
#> Number of spectra: 35
#> MSn retention times: 45:27 - 45:30 minutes
#> - - - Processing information - - -
#> Data loaded [Tue Aug 26 11:37:51 2025]
#> Filter: select parent/children scans for 21945 [Tue Aug 26 11:37:52 2025]
#> MSnbase version: 2.35.2
#> - - - Meta data - - -
#> phenoData
#> rowNames: MS3TMT11.mzML
#> varLabels: sampleNames
#> varMetadata: labelDescription
#> Loaded from:
#> MS3TMT11.mzML
#> protocolData: none
#> featureData
#> featureNames: F1.S001 F1.S002 ... F1.S035 (35 total)
#> fvarLabels: fileIdx spIdx ... spectrum (36 total)
#> fvarMetadata: labelDescription
#> experimentData: use 'experimentData(object)'
table(msLevel(from1))
#>
#> 1 2 3
#> 1 17 17
## Extract the second sepctrum's parent (MS1) and children (MS3)
## spectra
(from2 <- filterPrecursorScan(odmse, 21946))
#> MSn experiment data ("OnDiskMSnExp")
#> Object size in memory: 0.03 Mb
#> - - - Spectra data - - -
#> MS level(s): 1 2 3
#> Number of spectra: 3
#> MSn retention times: 45:27 - 45:27 minutes
#> - - - Processing information - - -
#> Data loaded [Tue Aug 26 11:37:51 2025]
#> Filter: select parent/children scans for 21946 [Tue Aug 26 11:37:52 2025]
#> MSnbase version: 2.35.2
#> - - - Meta data - - -
#> phenoData
#> rowNames: MS3TMT11.mzML
#> varLabels: sampleNames
#> varMetadata: labelDescription
#> Loaded from:
#> MS3TMT11.mzML
#> protocolData: none
#> featureData
#> featureNames: F1.S001 F1.S002 F1.S004
#> fvarLabels: fileIdx spIdx ... spectrum (36 total)
#> fvarMetadata: labelDescription
#> experimentData: use 'experimentData(object)'
table(msLevel(from2))
#>
#> 1 2 3
#> 1 1 1