OnDiskMSnExp Class for MS Data And Meta-DataOnDiskMSnExp-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.
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 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.
backend:Character string specifying the used backend.
spectraProcessingQueue:list of ProcessingStep objects
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)
See phenoData for more details.
Slot is inherited from "pSet".
featureData:Object of class
"AnnotatedDataFrame" containing variables
describing features (spectra in our case). See
featureData for more details.
Slot is inherited from "pSet".
experimentData:Object of class
"MIAPE", containing details of experimental
methods. See experimentData for more details.
Slot is inherited from "pSet".
protocolData:Object of class
"AnnotatedDataFrame" containing
equipment-generated variables (inherited from
"eSet"). See protocolData for
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" and
MSnExp of the current instance.
Slot is inherited from "pSet".
Intended for developer use and debugging (inherited from
"eSet").
Class "MSnExp", directly.
Class "pSet", by class "MSnExp", distance 3.
Class "VersionedBiobase", by class "pSet", distance 4.
Class "Versioned", by class "pSet", distance 5.
(in alphabetical order)
See also methods for MSnExp or
pSet objects.
object[i]:subset the OnDiskMSnExp by
spectra. i can be a numeric or logical
vector specifying to which spectra the data set should be reduced
(with i being the index of the spectrum in the object's
featureData).
The method returns a OnDiskMSnExp object with the data
sub-set.
object[[i]]: extract s single spectrum from the
OnDiskMSnExp object object. Argument i can be
either numeric or character specifying the index or the name of
the spectrum in the object (i.e. in the featureData). The
relevant information will be extracted from the corresponding raw
data file.
The method returns a Spectrum1 object.
acquisitionNum(signature(object="OnDiskMSnExp")): get the
acquisition number of each spectrum in each individual file. The
relevant information is extracted from the object's
featureData slot.
Returns a numeric vector with names corresponding to the spectrum names.
assayData(signature(object = "OnDiskMSnExp")):
Extract the full data, i.e. read all spectra from the original files,
apply all processing steps from the spectraProcessingQueue
slot and return the data. Due to the required processing time
accessing the full data should be avoided wherever possible.
Returns an environment.
centroided(signature(object="OnDiskMSnExp", msLevel, =
"numeric")): whether individual spectra are centroided or
uncentroided. The relevant information is extracted from the
object's featureData slot. Returns a logical vector with
names corresponding to the spectrum names. Use
centroided(object) <- value to 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 object
are in profile or centroided mode. The function takes the
qtlth quantile top peaks, then calculates the difference
between adjacent M/Z value and returns TRUE if the first
quartile is greater than k. (See
MSnbase:::.isCentroided for the code.) If verbose
(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 isCentroidedFromFile that accessed the mode
directly from the raw data file.
fromFile(signature(object = "OnDiskMSnExp")): get the
index of the file (in fileNames(object)) from which the
spectra were read. The relevant information is extracted from the
object's featureData slot.
Returns a numeric vector with names corresponding to the spectrum names.
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
the spectraProcessingQueue). To reduce the amount of
required memory, this is performed on a per-file basis.
The BPPARAM argument 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 list of numeric intensity values. Each
list element represents the intensities from one spectrum.
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).
The BPPARAM argument 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(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 NA if
not specified in the original file.
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 NA if
not specified in the original file.
length(signature(object="OnDiskMSnExp")):
Returns the number of spectra of the current experiment.
msLevel(signature(object = "OnDiskMSnExp")): extract the
MS level from the spectra. The relevant information is extracted
from the object's featureData slot.
Returns a numeric vector with names corresponding to the spectrum names.
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
the spectraProcessingQueue). To reduce the amount of
required memory, this is performed on a per-file basis.
The BPPARAM argument 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 list of numeric M/Z values. Each
list element represents the values from one spectrum.
peaksCount(signature(object="OnDiskMSnExp",
scans="numeric"), BPPARAM=bpparam()):
extrac the peaks count from each spectrum in the object. Depending
on the eventually present ProcessingStep objects in the
spectraProcessingQueue raw data will be loaded to calculate
the peaks count. If no steps are present, the data is extracted
from the featureData. Optional argument scans allows
to specify the index of specific spectra from which the count
should be returned. The BPPARAM argument 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(signature(object="OnDiskMSnExp")):
returns a numeric vector with the polarity of the individual
spectra in the data set. The relevant information is extracted
from the featureData.
rtime(signature(object="OnDiskMSnExp")):
extrac the retention time of the individual spectra in the data
set (from the featureData).
Returns a numeric vector with names corresponding to the spectrum names.
scanIndex(signature(object="OnDiskMSnExp")):
get the spectra scan indices within the respective file. The
relevant information is extracted from the object's featureData slot.
Returns a numeric vector of indices with names corresponding to the
spectrum names.
smoothed(signature(object="OnDiskMSnExp", msLevel. =
"numeric")): whether individual spectra are smoothed or
unsmoothed. The relevant information is extracted from the
object's featureData slot. Returns a logical vector with
names corresponding to the spectrum names. Use
smoothed(object) <- value to update the information, with
value being a logical vector of length equal to the number of
spectra in the experiment.
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 the spectraProcessingQueue
are applied to it. The results are then returned as a list
of Spectrum1 objects.
The BPPARAM argument 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 list of Spectrum1 objects
with names corresponding to the spectrum names.
tic(signature(object="OnDiskMSnExp"), initial = TRUE,
BPPARAM = bpparam()):
get the total ion current (TIC) of each spectrum in the data
set. If initial = TRUE, the information is extracted from
the object's featureData and represents the tic provided in
the header of the original raw data files. For initial =
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.
BPPARAM parameter: see spectra method above.
Returns a numeric vector with names corresponding to the spectrum names.
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. If initial = TRUE, the
information is extracted from the object's featureData and
represents the bpi provided in the header of the original raw data
files. For initial = 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.
BPPARAM parameter: see spectra method above.
Returns a numeric vector with names corresponding to the spectrum names.
tic(signature(object="OnDiskMSnExp")): return a
character of length length(object) containing the
feature names. A replacement method is also available.
spectrapply(signature(object = "OnDiskMSnExp"), FUN = NULL,
BPPARAM = bpparam(), ...): applies the function FUN to each
spectrum passing additional parameters in ... to that
function and return its results. For FUN = NULL it returns
the list of spectra (same as a call to spectra). Parameter
BPPARAM allows to specify how and if parallel processing
should be enabled.
Returns a list with the result for each of spectrum.
(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(signature(object="OnDiskMSnExp"), all=TRUE, verbose=TRUE):
add an clean processing step to the lazy processing queue
of the OnDiskMSnExp object. The clean command will
only be executed when spectra information (including M/Z and
intensity values) is requested from the OnDiskMSnExp
object. Optional arguments to the methods are all=TRUE and
verbose=TRUE.
The method returns an OnDiskMSnExp object.
For more details see documentation of the clean
method.
normalize(signature(object="OnDiskMSnExp"), method=c("max",
"sum"), ...):
add a normalize processing step to the lazy processing
queue of the returned OnDiskMSnExp object.
The method returns an OnDiskMSnExp object.
For more details see documentation of the
normalize method.
removePeaks(signature(object="OnDiskMSnExp"), t="min", verbose=TRUE):
add a removePeaks processing step to the lazy processing
queue of the returned OnDiskMSnExp object.
The method returns an OnDiskMSnExp object.
For more details see documentation of the removePeaks
method.
trimMz(signature(object="OnDiskMSnExp", mzlim="numeric"),...):
add a trimMz processing step to the lazy processing queue
of the returned OnDiskMSnExp object.
The method returns an OnDiskMSnExp object.
For more details see documentation of the trimMz
method.
validateOnDiskMSnExp(signature(object = "OnDiskMSnExp")):
validates an OnDiskMSnExp object and all of its spectra. In
addition to the standard validObject method, this
method reads also all spectra from the original files, applies
eventual processing steps and evaluates their validity.
as(from, "MSnExp")Converts the OnDiskMSnExp
object from, to an in-memory MSnExp. Also available
as an S3 method as.MSnExp().
## 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 [Wed Sep 11 07:29:40 2024]
#> Filter: select parent/children scans for 21945 [Wed Sep 11 07:29:41 2024]
#> MSnbase version: 2.31.1
#> - - - 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 (35 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 [Wed Sep 11 07:29:40 2024]
#> Filter: select parent/children scans for 21946 [Wed Sep 11 07:29:41 2024]
#> MSnbase version: 2.31.1
#> - - - 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 (35 total)
#> fvarMetadata: labelDescription
#> experimentData: use 'experimentData(object)'
table(msLevel(from2))
#>
#> 1 2 3
#> 1 1 1