Description Usage Arguments Value Backend functions Subsetting and merging backend classes MsBackendDataFrame, in-memory MS data backend MsBackendMzR, on-disk MS data backend MsBackendHdf5Peaks, on-disk MS data backend Implementation notes Author(s) Examples
Note that the classes described here are not meant to be used directly by the end-users and the material in this man page is aimed at package developers.
MsBackend
is a virtual class that defines what each different
backend needs to provide. MsBackend
objects provide access to
mass spectrometry data. Such backends can be classified into
in-memory or on-disk backends, depending on where the data, i.e
spectra (m/z and intensities) and spectra annotation (MS level,
charge, polarity, ...) are stored.
Typically, in-memory backends keep all data in memory ensuring fast data access, while on-disk backends store (parts of) their data on disk and retrieve it on demand.
The Backend functions and implementation notes for new backend classes section documents the API that a backend must implement.
Currently available backends are:
MsBackendDataFrame
: stores all data in memory using a DataFrame
.
MsBackendMzR
: stores the m/z and intensities on-disk in raw
data files (typically mzML
or mzXML
) and the spectra
annotation information (header) in memory in a DataFrame
. This
backend requires the mzR
package.
MsBackendHdf5Peaks
: stores the m/z and intensities on-disk in custom hdf5
data files and the remaining spectra variables in memory (in a
DataFrame
). This backend requires the rhdf5
package.
See below for more details about individual backends.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | ## S4 method for signature 'MsBackend'
backendInitialize(object, ...)
## S4 method for signature 'list'
backendMerge(object, ...)
## S4 method for signature 'MsBackend'
backendMerge(object, ...)
## S4 method for signature 'MsBackend'
export(object, ...)
## S4 method for signature 'MsBackend'
acquisitionNum(object)
## S4 method for signature 'MsBackend'
peaksData(object)
## S4 method for signature 'MsBackend'
centroided(object)
## S4 replacement method for signature 'MsBackend'
centroided(object) <- value
## S4 method for signature 'MsBackend'
collisionEnergy(object)
## S4 replacement method for signature 'MsBackend'
collisionEnergy(object) <- value
## S4 method for signature 'MsBackend'
dataOrigin(object)
## S4 replacement method for signature 'MsBackend'
dataOrigin(object) <- value
## S4 method for signature 'MsBackend'
dataStorage(object)
## S4 replacement method for signature 'MsBackend'
dataStorage(object) <- value
## S4 method for signature 'MsBackend'
dropNaSpectraVariables(object)
## S4 method for signature 'MsBackend'
filterAcquisitionNum(object, n, file, ...)
## S4 method for signature 'MsBackend'
filterDataOrigin(object, dataOrigin = character())
## S4 method for signature 'MsBackend'
filterDataStorage(object, dataStorage = character())
## S4 method for signature 'MsBackend'
filterEmptySpectra(object, ...)
## S4 method for signature 'MsBackend'
filterIsolationWindow(object, mz = numeric(), ...)
## S4 method for signature 'MsBackend'
filterMsLevel(object, msLevel = integer())
## S4 method for signature 'MsBackend'
filterPolarity(object, polarity = integer())
## S4 method for signature 'MsBackend'
filterPrecursorMz(object, mz = numeric())
## S4 method for signature 'MsBackend'
filterPrecursorScan(object, acquisitionNum = integer())
## S4 method for signature 'MsBackend'
filterRt(object, rt = numeric(), msLevel. = unique(msLevel(object)))
## S4 method for signature 'MsBackend'
intensity(object)
## S4 replacement method for signature 'MsBackend'
intensity(object) <- value
## S4 method for signature 'MsBackend'
ionCount(object)
## S4 method for signature 'MsBackend'
isCentroided(object, ...)
## S4 method for signature 'MsBackend'
isEmpty(x)
## S4 method for signature 'MsBackend'
isolationWindowLowerMz(object)
## S4 replacement method for signature 'MsBackend'
isolationWindowLowerMz(object) <- value
## S4 method for signature 'MsBackend'
isolationWindowTargetMz(object)
## S4 replacement method for signature 'MsBackend'
isolationWindowTargetMz(object) <- value
## S4 method for signature 'MsBackend'
isolationWindowUpperMz(object)
## S4 replacement method for signature 'MsBackend'
isolationWindowUpperMz(object) <- value
## S4 method for signature 'MsBackend'
isReadOnly(object)
## S4 method for signature 'MsBackend'
length(x)
## S4 method for signature 'MsBackend'
msLevel(object)
## S4 method for signature 'MsBackend'
mz(object)
## S4 replacement method for signature 'MsBackend'
mz(object) <- value
## S4 method for signature 'MsBackend'
lengths(x, use.names = FALSE)
## S4 method for signature 'MsBackend'
polarity(object)
## S4 replacement method for signature 'MsBackend'
polarity(object) <- value
## S4 method for signature 'MsBackend'
precScanNum(object)
## S4 method for signature 'MsBackend'
precursorCharge(object)
## S4 method for signature 'MsBackend'
precursorIntensity(object)
## S4 method for signature 'MsBackend'
precursorMz(object)
## S4 replacement method for signature 'MsBackend'
peaksData(object) <- value
## S4 method for signature 'MsBackend'
reset(object)
## S4 method for signature 'MsBackend'
rtime(object)
## S4 replacement method for signature 'MsBackend'
rtime(object) <- value
## S4 method for signature 'MsBackend'
scanIndex(object)
## S4 method for signature 'MsBackend'
selectSpectraVariables(object, spectraVariables = spectraVariables(object))
## S4 method for signature 'MsBackend'
smoothed(object)
## S4 replacement method for signature 'MsBackend'
smoothed(object) <- value
## S4 method for signature 'MsBackend'
spectraData(object, columns = spectraVariables(object))
## S4 replacement method for signature 'MsBackend'
spectraData(object) <- value
## S4 method for signature 'MsBackend'
spectraNames(object)
## S4 replacement method for signature 'MsBackend'
spectraNames(object) <- value
## S4 method for signature 'MsBackend'
spectraVariables(object)
## S4 method for signature 'MsBackend,ANY'
split(x, f, drop = FALSE, ...)
## S4 method for signature 'MsBackend'
tic(object, initial = TRUE)
## S4 method for signature 'MsBackend'
x[i, j, ..., drop = FALSE]
## S4 method for signature 'MsBackend'
x$name
## S4 replacement method for signature 'MsBackend'
x$name <- value
MsBackendDataFrame()
## S4 method for signature 'MsBackendDataFrame'
backendInitialize(object, data, ...)
MsBackendHdf5Peaks()
MsBackendMzR()
|
object |
Object extending |
... |
Additional arguments. |
value |
replacement value for |
n |
for |
file |
For |
dataOrigin |
For |
dataStorage |
For |
mz |
For |
msLevel |
|
polarity |
For |
acquisitionNum |
for |
rt |
for |
msLevel. |
same as |
x |
Object extending |
use.names |
For |
spectraVariables |
For |
columns |
For |
f |
|
drop |
For |
initial |
For |
i |
For |
j |
For |
name |
For |
data |
For |
See documentation of respective function.
New backend classes must extend the base MsBackend
class and
have to implement the following methods:
[
: subset the backend. Only subsetting by element (row/i
) is
allowed
$
, $<-
: access or set/add a single spectrum variable (column) in the
backend.
acquisitionNum
: returns the acquisition number of each
spectrum. Returns an integer
of length equal to the number of
spectra (with NA_integer_
if not available).
peaksData
returns a list
with the spectras' peak data. The length of
the list is equal to the number of spectra in object
. Each element of
the list is a matrix
with columns "mz"
and "intensity"
. For an empty
spectrum, a matrix
with 0 rows and two columns (named mz
and
intensity
) is returned.
backendInitialize
: initialises the backend. This method is
supposed to be called rights after creating an instance of the
backend class and should prepare the backend (e.g. set the data
for the memory backend or read the spectra header data for the
MsBackendMzR
backend). This method has to ensure to set the
spectra variable dataStorage
correctly.
backendMerge
: merges (combines) MsBackend
objects into a single
instance. All objects to be merged have to be of the same type (e.g.
MsBackendDataFrame()
).
dataOrigin
: gets a character
of length equal to the number of spectra
in object
with the data origin of each spectrum. This could e.g. be
the mzML file from which the data was read.
dataStorage
: gets a character
of length equal to the number of spectra
in object
with the data storage of each spectrum. Note that a
dataStorage
of NA_character_
is not supported.
dropNaSpectraVariables
: removes spectra variables (i.e. columns in the
object's spectraData
that contain only missing values (NA
). Note that
while columns with only NA
s are removed, a spectraData
call after
dropNaSpectraVariables
might still show columns containing NA
values
for core spectra variables.
centroided
, centroided<-
: gets or sets the centroiding
information of the spectra. centroided
returns a logical
vector of length equal to the number of spectra with TRUE
if a
spectrum is centroided, FALSE
if it is in profile mode and NA
if it is undefined. See also isCentroided
for estimating from
the spectrum data whether the spectrum is centroided. value
for centroided<-
is either a single logical
or a logical
of
length equal to the number of spectra in object
.
collisionEnergy
, collisionEnergy<-
: gets or sets the
collision energy for all spectra in object
. collisionEnergy
returns a numeric
with length equal to the number of spectra
(NA_real_
if not present/defined), collisionEnergy<-
takes a
numeric
of length equal to the number of spectra in object
.
export
: exports data from a Spectra
class to a file. This method is
called by the export,Spectra
method that passes itself as a second
argument to the function. The export,MsBackend
implementation is thus
expected to take a Spectra
class as second argument from which all data
is exported. Taking data from a Spectra
class ensures that also all
eventual data manipulations (cached in the Spectra
's lazy evaluation
queue) are applied prior to export - this would not be possible with only a
MsBackend class. An example implementation is the export
method
for the MsBackendMzR
backend that supports export of the data in
mzML or mzXML format. See the documentation for the MsBackendMzR
class below for more information.
filterAcquisitionNum
: filters the object keeping only spectra matching
the provided acquisition numbers (argument n
). If dataOrigin
or
dataStorage
is also provided, object
is subsetted to the spectra with
an acquisition number equal to n
in spectra with matching dataOrigin
or dataStorage values retaining all other spectra.
filterDataOrigin
: filters the object retaining spectra matching the
provided dataOrigin
. Parameter dataOrigin
has to be of type
character
and needs to match exactly the data origin value of the
spectra to subset.
filterDataOrigin
should return the data ordered by the provided
dataOrigin
parameter, i.e. if dataOrigin = c("2", "1")
was provided,
the spectra in the resulting object should be ordered accordingly (first
spectra from data origin "2"
and then from "1"
).
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterDataStorage
: filters the object retaining spectra matching the
provided dataStorage
. Parameter dataStorage
has to be of type
character
and needs to match exactly the data storage value of the
spectra to subset.
filterDataStorage
should return the data ordered by the provided
dataStorage
parameter, i.e. if dataStorage = c("2", "1")
was provided,
the spectra in the resulting object should be ordered accordingly (first
spectra from data storage "2"
and then from "1"
).
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterEmptySpectra
: removes empty spectra (i.e. spectra without peaks).
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterFile
: retains data of files matching the file index or file name
provided with parameter file
.
filterIsolationWindow
: retains spectra that contain mz
in their
isolation window m/z range (i.e. with an isolationWindowLowerMz
<=
mz
and isolationWindowUpperMz
>=
mz
.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterMsLevel
: retains spectra of MS level msLevel
.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterPolarity
: retains spectra of polarity polarity
.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterPrecursorMz
: retains spectra with a precursor m/z within the
provided m/z range.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterPrecursorScan
: retains parent (e.g. MS1) and children scans (e.g.
MS2) of acquisition number acquisitionNum
.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
filterRt
: retains spectra of MS level msLevel
with retention times
within (>=
) rt[1]
and (<=
) rt[2]
.
Implementation of this method is optional since a default implementation
for MsBackend
is available.
intensity
: gets the intensity values from the spectra. Returns
a NumericList()
of numeric
vectors (intensity values for each
spectrum). The length of the list
is equal to the number of
spectra
in object
.
intensity<-
: replaces the intensity values. value
has to be a list
(or NumericList()
) of length equal to the number of spectra and the
number of values within each list element identical to the number of
peaks in each spectrum (i.e. the lengths(x)
). Note that just
writeable backends support this method.
ionCount
: returns a numeric
with the sum of intensities for
each spectrum. If the spectrum is empty (see isEmpty
),
NA_real_
is returned.
isCentroided
: a heuristic approach assessing if the spectra in
object
are in profile or centroided mode. The function takes
the qtl
th quantile top peaks, then calculates the difference
between adjacent m/z value and returns TRUE
if the first
quartile is greater than k
. (See Spectra:::.isCentroided
for
the code.)
isEmpty
: checks whether a spectrum in object
is empty
(i.e. does not contain any peaks). Returns a logical
vector of
length equal number of spectra.
isolationWindowLowerMz
, isolationWindowLowerMz<-
: gets or sets the
lower m/z boundary of the isolation window.
isolationWindowTargetMz
, isolationWindowTargetMz<-
: gets or sets the
target m/z of the isolation window.
isolationWindowUpperMz
, isolationWindowUpperMz<-
: gets or sets the
upper m/z boundary of the isolation window.
isReadOnly
: returns a logical(1)
whether the backend is read
only or does allow also to write/update data.
length
: returns the number of spectra in the object.
lengths
: gets the number of peaks (m/z-intensity values) per
spectrum. Returns an integer
vector (length equal to the
number of spectra). For empty spectra, 0
is returned.
msLevel
: gets the spectra's MS level. Returns an integer
vector (of length equal to the number of spectra) with the MS
level for each spectrum (or NA_integer_
if not available).
mz
: gets the mass-to-charge ratios (m/z) from the
spectra. Returns a NumericList()
or length equal to the number of
spectra, each element a numeric
vector with the m/z values of
one spectrum.
mz<-
: replaces the m/z values. value
has to be a list
of length equal
to the number of spectra and the number of values within each list element
identical to the number of peaks in each spectrum (i.e. the
lengths(x)
). Note that just writeable backends support this method.
polarity
, polarity<-
: gets or sets the polarity for each
spectrum. polarity
returns an integer
vector (length equal
to the number of spectra), with 0
and 1
representing negative
and positive polarities, respectively. polarity<-
expects an
integer vector of length 1 or equal to the number of spectra.
precursorCharge
, precursorIntensity
, precursorMz
,
precScanNum
, precAcquisitionNum
: get the charge (integer
),
intensity (numeric
), m/z (numeric
), scan index (integer
)
and acquisition number (interger
) of the precursor for MS level
2 and above spectra from the object. Returns a vector of length equal to
the number of spectra in object
. NA
are reported for MS1
spectra of if no precursor information is available.
peaksData<-
replaces the peak data (m/z and intensity values) of the
backend. This method expects a list
of matrix
objects with columns
"mz"
and "intensity"
that has the same length as the number of
spectra in the backend. Note that just writeable backends support this
method.
reset
a backend (if supported). This method will be called on the backend
by the reset,Spectra
method that is supposed to restore the data to its
original state (see reset,Spectra
for more details). The function
returns the reset backend. The default implementation for MsBackend
returns the backend as-is.
rtime
, rtime<-
: gets or sets the retention times for each
spectrum (in seconds). rtime
returns a numeric
vector (length equal to
the number of spectra) with the retention time for each spectrum.
rtime<-
expects a numeric vector with length equal to the
number of spectra.
scanIndex
: returns an integer
vector with the scan index
for each spectrum. This represents the relative index of the
spectrum within each file. Note that this can be different to the
acquisitionNum
of the spectrum which is the index of the
spectrum as reported in the mzML file.
selectSpectraVariables
: reduces the information within the backend to
the selected spectra variables.
smoothed
,smoothed<-
: gets or sets whether a spectrum is
smoothed. smoothed
returns a logical
vector of length equal
to the number of spectra. smoothed<-
takes a logical
vector
of length 1 or equal to the number of spectra in object
.
spectraData
, spectraData<-
: gets or sets general spectrum
metadata (annotation, also called header). spectraData
returns
a DataFrame
, spectraData<-
expects a DataFrame
with the same number
of rows as there are spectra in object
. Note that spectraData
has to
return the full data, i.e. also the m/z and intensity values (as a list
or SimpleList
in columns "mz"
and "intensity"
.
spectraNames
: returns a character
vector with the names of
the spectra in object
.
spectraVariables
: returns a character
vector with the
available spectra variables (columns, fields or attributes)
available in object
. This should return all spectra variables which
are present in object
, also "mz"
and "intensity"
(which are by
default not returned by the spectraVariables,Spectra
method).
split
: splits the backend into a list
of backends (depending on
parameter f
). The default method for MsBackend
uses split.default()
,
thus backends extending MsBackend
don't necessarily need to implement
this method.
tic
: gets the total ion current/count (sum of signal of a
spectrum) for all spectra in object
. By default, the value
reported in the original raw data file is returned. For an empty
spectrum, NA_real_
is returned.
Backend classes must support (implement) the [
method to subset the object.
This method should only support subsetting by spectra (rows, i
) and has
to return a MsBackend
class.
Backends extending MsBackend
should also implement the backendMerge
method to support combining backend instances (only backend classes of the
same type should be merged). Merging should follow the following rules:
The whole spectrum data of the various objects should be merged. The
resulting merged object should contain the union of the individual objects'
spectra variables (columns/fields), with eventually missing variables in
one object being filled with NA
.
MsBackendDataFrame
, in-memory MS data backendThe MsBackendDataFrame
objects keep all MS data in memory.
New objects can be created with the MsBackendDataFrame()
function. The backend can be subsequently initialized with the
backendInitialize
method, taking a DataFrame
with the MS data
as parameter. Suggested columns of this DataFrame
are:
"msLevel"
: integer
with MS levels of the spectra.
"rt"
: numeric
with retention times of the spectra.
"acquisitionNum"
: integer
with the acquisition number of the spectrum.
"scanIndex"
: integer
with the index of the scan/spectrum within the
mzML/mzXML/CDF file.
"dataOrigin"
: character
defining the data origin.
"dataStorage"
: character
indicating grouping of spectra in different
e.g. input files. Note that missing values are not supported.
"centroided"
: logical
whether the spectrum is centroided.
"smoothed"
: logical
whether the spectrum was smoothed.
"polarity"
: integer
with the polarity information of the spectra.
"precScanNum"
: integer
specifying the index of the (MS1) spectrum
containing the precursor of a (MS2) spectrum.
"precursorMz"
: numeric
with the m/z value of the precursor.
"precursorIntensity"
: numeric
with the intensity value of the
precursor.
"precursorCharge"
: integer
with the charge of the precursor.
"collisionEnergy"
: numeric
with the collision energy.
"mz"
: NumericList()
of numeric
vectors representing the m/z values
for each spectrum.
"intensity"
: NumericList()
of numeric
vectors representing the
intensity values for each spectrum.
Additional columns are allowed too.
MsBackendMzR
, on-disk MS data backendThe MsBackendMzR
keeps only a limited amount of data in memory,
while the spectra data (m/z and intensity values) are fetched from
the raw files on-demand. This backend uses the mzR
package for
data import and retrieval and hence requires that package to be
installed. Also, it can only be used to import and represent data
stored in mzML, mzXML and CDF files.
The MsBackendMzR
backend extends the MsBackendDataFrame
backend using
its DataFrame
to keep spectra variables (except m/z and intensity) in
memory.
New objects can be created with the MsBackendMzR()
function which
can be subsequently filled with data by calling backendInitialize
passing the file names of the input data files with argument files
.
This backend provides an export
method to export data from a Spectra
in
mzML or mzXML format. The definition of the function is:
export(object, x, file = tempfile(), format = c("mzML", "mzXML"), copy = FALSE)
The parameters are:
object
: an instance of the MsBackendMzR
class.
x
: the Spectra object to be exported.
file
: character
with the (full) output file name(s). Should be
of length 1 or equal length(x)
. If a single file is specified, all
spectra are exported to that file. Alternatively it is possible to specify
for each spectrum in x
the name of the file to which it should be
exported (and hence file
has to be of length equal length(x)
).
format
: character(1)
, either "mzML"
or "mzXML"
defining the output
file format.
copy
: logical(1)
whether general file information should be copied from
the original MS data files. This only works if x
uses a MsBackendMzR
backend and if dataOrigin(x)
contains the original MS data file names.
BPPARAM
: parallel processing settings.
See examples in Spectra or the vignette for more details and examples.
MsBackendHdf5Peaks
, on-disk MS data backendThe MsBackendHdf5Peaks
keeps, similar to the MsBackendMzR
, peak data
(i.e. m/z and intensity values) in custom data files (in HDF5 format) on
disk while the remaining spectra variables are kept in memory. This backend
supports updating and writing of manipulated peak data to the data files.
New objects can be created with the MsBackendHdf5Peaks()
function which
can be subsequently filled with data by calling the object's
backendInitialize
method passing the desired file names of the HDF5 data
files along with the spectra variables in form of a DataFrame
(see
MsBackendDataFrame
for the expected format). An optional parameter
hdf5path
allows to specify the folder where the HDF5 data files should be
stored to. If provided, this is added as the path to the submitted file
names (parameter files
).
By default backendInitialize
will store all peak data into a single HDF5
file which name has to be provided with the parameter files
. To store peak
data across several HDF5 files data
has to contain a column
"dataStorage"
that defines the grouping of spectra/peaks into files: peaks
for spectra with the same value in "dataStorage"
are saved into the same
HDF5 file. If parameter files
is omitted, the value in dataStorage
is
used as file name (replacing any file ending with ".h5"
. To specify the
file names, files
' length has to match the number of unique elements in
"dataStorage"
.
For details see examples on the Spectra()
help page.
Backends extending MsBackend
must implement all of its methods (listed
above). Developers of new MsBackend
s should follow the
MsBackendDataFrame
implementation.
The MsBackend
defines the following slots:
@readonly
: logical(1)
whether the backend supports writing/replacing
of m/z or intensity values.
Johannes Rainer, Sebastian Gibb, Laurent Gatto
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | ## The MsBackend class is a virtual class and can not be instantiated
## directly. Below we define a new backend class extending this virtual
## class
MsBackendDummy <- setClass("MsBackendDummy", contains = "MsBackend")
MsBackendDummy()
## This class inherits now all methods from `MsBackend`, all of which
## however throw an error. These methods would have to be implemented
## for the new backend class.
try(mz(MsBackendDummy()))
## See `MsBackendDataFrame` as a reference implementation for a backend
## class (in the *R/MsBackendDataFrame.R* file).
## MsBackendDataFrame
##
## The `MsBackendDataFrame` uses a `S4Vectors::DataFrame` to store all MS
## data. Below we create such a backend by passing a `DataFrame` with all
## data to it.
data <- DataFrame(msLevel = c(1L, 2L, 1L), scanIndex = 1:3)
data$mz <- list(c(1.1, 1.2, 1.3), c(1.4, 54.2, 56.4, 122.1), c(15.3, 23.2))
data$intensity <- list(c(3, 2, 3), c(45, 100, 12.2, 1), c(123, 12324.2))
## Backends are supposed to be created with their specific constructor
## function
be <- MsBackendDataFrame()
be
## The `backendInitialize` method initializes the backend filling it with
## data. This method can take any parameters needed for the backend to
## get loaded with the data (e.g. a file name from which to load the data,
## a database connection or, in this case, a data frame containing the data).
be <- backendInitialize(be, data)
be
## Data can be accessed with the accessor methods
msLevel(be)
mz(be)
## Even if no data was provided for all spectra variables, its accessor
## methods are supposed to return a value.
precursorMz(be)
## The `peaksData` method is supposed to return the peaks of the spectra as
## a `list`.
peaksData(be)
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