spectraData: Accessing mass spectrometry data
In rformassspectrometry/Spectra: Spectra Infrastructure for Mass Spectrometry Data
spectraData R Documentation
Accessing mass spectrometry data
Description
As detailed in the documentation of the Spectra class, a Spectra object
is a container for mass spectrometry (MS) data that includes both the mass
peaks data (or peaks data, generally m/z and intensity values) as well
as spectra metadata (so called spectra variables). Spectra variables
generally define one value per spectrum, while for peaks variables one value
per mass peak is defined and hence multiple values per spectrum (depending
on the number of mass peaks of a spectrum).
Data can be extracted from a Spectra object using dedicated accessor
functions or also using the $ operator. Depending on the backend class
used by the Spectra to represent the data, data can also be added or
replaced (again, using dedicated functions or using $<-).
Usage
asDataFrame(
object,
i = seq_along(object),
spectraVars = spectraVariables(object)
)
## S4 method for signature 'Spectra'
acquisitionNum(object)
## S4 method for signature 'Spectra'
centroided(object)
## S4 replacement method for signature 'Spectra'
centroided(object) <- value
## S4 method for signature 'Spectra'
collisionEnergy(object)
## S4 replacement method for signature 'Spectra'
collisionEnergy(object) <- value
coreSpectraVariables()
## S4 method for signature 'Spectra'
dataOrigin(object)
## S4 replacement method for signature 'Spectra'
dataOrigin(object) <- value
## S4 method for signature 'Spectra'
dataStorage(object)
## S4 method for signature 'Spectra'
intensity(object, f = processingChunkFactor(object), ...)
## S4 method for signature 'Spectra'
ionCount(object)
## S4 method for signature 'Spectra'
isCentroided(object, ...)
## S4 method for signature 'Spectra'
isEmpty(x)
## S4 method for signature 'Spectra'
isolationWindowLowerMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowLowerMz(object) <- value
## S4 method for signature 'Spectra'
isolationWindowTargetMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowTargetMz(object) <- value
## S4 method for signature 'Spectra'
isolationWindowUpperMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowUpperMz(object) <- value
## S4 method for signature 'Spectra'
length(x)
## S4 method for signature 'Spectra'
lengths(x, use.names = FALSE)
## S4 method for signature 'Spectra'
msLevel(object)
## S4 method for signature 'Spectra'
mz(object, f = processingChunkFactor(object), ...)
## S4 method for signature 'Spectra'
peaksData(
object,
columns = c("mz", "intensity"),
f = processingChunkFactor(object),
...,
BPPARAM = bpparam()
)
## S4 method for signature 'Spectra'
peaksVariables(object)
## S4 method for signature 'Spectra'
polarity(object)
## S4 replacement method for signature 'Spectra'
polarity(object) <- value
## S4 method for signature 'Spectra'
precScanNum(object)
## S4 method for signature 'Spectra'
precursorCharge(object)
## S4 method for signature 'Spectra'
precursorIntensity(object)
## S4 method for signature 'Spectra'
precursorMz(object)
## S4 method for signature 'Spectra'
rtime(object)
## S4 replacement method for signature 'Spectra'
rtime(object) <- value
## S4 method for signature 'Spectra'
scanIndex(object)
## S4 method for signature 'Spectra'
smoothed(object)
## S4 replacement method for signature 'Spectra'
smoothed(object) <- value
## S4 method for signature 'Spectra'
spectraData(object, columns = spectraVariables(object))
## S4 replacement method for signature 'Spectra'
spectraData(object) <- value
## S4 method for signature 'Spectra'
spectraNames(object)
## S4 replacement method for signature 'Spectra'
spectraNames(object) <- value
## S4 method for signature 'Spectra'
spectraVariables(object)
## S4 method for signature 'Spectra'
tic(object, initial = TRUE)
## S4 method for signature 'Spectra'
uniqueMsLevels(object, ...)
## S4 method for signature 'Spectra'
x$name
## S4 replacement method for signature 'Spectra'
x$name <- value
## S4 method for signature 'Spectra'
x[[i, j, ...]]
## S4 replacement method for signature 'Spectra'
x[[i, j, ...]] <- value
Arguments
object
A Spectra object.
i
For asDataFrame(): A numeric indicating which scans to coerce
to a DataFrame (default is seq_along(object)).
spectraVars
character() indicating what spectra variables to add to
the DataFrame. Default is spectraVariables(object), i.e. all
available variables.
value
A vector with values to replace the respective spectra
variable. Needs to be of the correct data type for the spectra variable.
f
For intensity(), mz() and peaksData(): factor defining how
data should be chunk-wise loaded an processed. Defaults to
processingChunkFactor().
...
Additional arguments.
x
A Spectra object.
use.names
For lengths(): ignored.
columns
For spectraData() accessor: optional character with
column names (spectra variables) that should be included in the
returned DataFrame. By default, all columns are returned.
For peaksData() accessor: optional character with requested columns
in the individual matrix of the returned list. Defaults to
c("mz", "value") but any values returned by peaksVariables(object)
with object being the Spectra object are supported.
BPPARAM
Parallel setup configuration. See bpparam() for more
information. See also processingChunkSize() for more information
on parallel processing.
initial
For tic(): logical(1) whether the initially
reported total ion current should be reported, or whether the
total ion current should be (re)calculated on the actual data
(initial = FALSE, same as ionCount()).
name
For $ and $<-: the name of the spectra variable to return
or set.
j
For [: not supported.
Spectra variables
A common set of core spectra variables are defined for Spectra. These
have a pre-defined data type and each Spectra will return a value for
these if requested. If no value for a spectra variable is defined, a missing
value (of the correct data type) is returned. The list of core spectra
variables and their respective data type is:
-
acquisitionNum integer(1): the index of acquisition of a spectrum
during an MS run.
-
centroided logical(1): whether the spectrum is in profile or centroid
mode.
-
collisionEnergy numeric(1): collision energy used to create an MSn
spectrum.
-
dataOrigin character(1): the origin of the spectrum's data, e.g. the
mzML file from which it was read.
-
dataStorage character(1): the (current) storage location of the
spectrum data. This value depends on the backend used to handle and
provide the data. For an in-memory backend like the MsBackendDataFrame
this will be "<memory>", for an on-disk backend such as the
MsBackendHdf5Peaks it will be the name of the HDF5 file where the
spectrum's peak data is stored.
-
isolationWindowLowerMz numeric(1): lower m/z for the isolation
window in which the (MSn) spectrum was measured.
-
isolationWindowTargetMz numeric(1): the target m/z for the isolation
window in which the (MSn) spectrum was measured.
-
isolationWindowUpperMz numeric(1): upper m/z for the isolation window
in which the (MSn) spectrum was measured.
-
msLevel integer(1): the MS level of the spectrum.
-
polarity integer(1): the polarity of the spectrum (0 and 1
representing negative and positive polarity, respectively).
-
precScanNum integer(1): the scan (acquisition) number of the precursor
for an MSn spectrum.
-
precursorCharge integer(1): the charge of the precursor of an MSn
spectrum.
-
precursorIntensity numeric(1): the intensity of the precursor of an
MSn spectrum.
-
precursorMz numeric(1): the m/z of the precursor of an MSn spectrum.
-
rtime numeric(1): the retention time of a spectrum.
-
scanIndex integer(1): the index of a spectrum within a (raw) file.
-
smoothed logical(1): whether the spectrum was smoothed.
For each of these spectra variable a dedicated accessor function is defined
(such as msLevel() or rtime()) that allows to extract the values of
that spectra variable for all spectra in a Spectra object. Also,
replacement functions are defined, but not all backends might support
replacing values for spectra variables. As described above, additional
spectra variables can be defined or added. The spectraVariables() function
can be used to
Values for multiple spectra variables, or all spectra vartiables* can be
extracted with the spectraData() function.
Peaks variables
Spectra also provide mass peak data with the m/z and intensity values
being the core peaks variables:
-
intensity numeric: intensity values for the spectrum's peaks.
-
mz numeric: the m/z values for the spectrum's peaks.
Values for these can be extracted with the mz() and intensity()
functions, or the peaksData() function. The former functions return a
NumericList with the respective values, while the latter returns a List
with numeric two-column matrices. The list of peaks matrices can also
be extracted using as(x, "list") or as(x, "SimpleList") with x being
a Spectra object.
Some Spectra/backends provide also values for additional peaks variables.
The set of available peaks variables can be extracted with the
peaksVariables() function.
Functions to access MS data
The set of available functions to extract data from, or set data in, a
Spectra object are (in alphabetical order) listed below. Note that there
are also other functions to extract information from a Spectra object
documented in addProcessing().
-
$, $<-: gets (or sets) a spectra variable for all spectra in object.
See examples for details. Note that replacing values of a peaks variable
is not supported with a non-empty processing queue, i.e. if any filtering
or data manipulations on the peaks data was performed. In these cases
applyProcessing() needs to be called first to apply all cached data
operations.
-
[[, [[<-: 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).
-
asDataFrame(): converts the Spectra to a DataFrame (in long format)
contining all data. Returns a DataFrame.
-
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.
-
coreSpectraVariables(): returns the core spectra variables along with
their expected data type.
-
dataOrigin(), dataOrigin<-: gets or sets the data origin for each
spectrum. dataOrigin() returns a character vector (same length than
object) with the origin of the spectra. dataOrigin<- expects a
character vector (same length than object) with the replacement
values for the data origin of each spectrum.
-
dataStorage(): returns a character vector (same length than object)
with the data storage location of each spectrum.
-
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.
-
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 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 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.
-
length(): gets 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 (names
being spectrum names, length equal to the number of spectra) with the MS
level for each spectrum.
-
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.
-
peaksData(): gets the peaks data for all spectra in object. Peaks
data consist of the m/z and intensity values as well as possible additional
annotations (variables) of all peaks of each spectrum. The function
returns a SimpleList() of two dimensional arrays (either matrix or
data.frame), with each array providing the values for the requested
peak variables (by default "mz" and "intensity"). Optional parameter
columns is passed to the backend's peaksData() function to allow
the selection of specific (or additional) peaks variables (columns) that
should be extracted (if available). Importantly,
it is not guaranteed that each backend supports this parameter (while
each backend must support extraction of "mz" and "intensity" columns).
Parameter columns defaults to c("mz", "intensity") but any value
returned by peaksVariables(object) is supported.
Note also that it is possible to extract the peak data with
as(x, "list") and as(x, "SimpleList") as a list and SimpleList,
respectively. Note however that, in contrast to peaksData(), as()
does not support the parameter columns.
-
peaksVariables(): lists the available variables for mass peaks provided
by the backend. Default peak variables are "mz" and "intensity" (which
all backends need to support and provide), but some backends might provide
additional variables.
These variables correspond to the column names of the peak data array
returned by peaksData().
-
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(): gets the charge (integer),
intensity (numeric), m/z (numeric), scan index (integer)
and acquisition number (interger) of the precursor for MS level >
2 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.
-
rtime(), rtime<-: gets or sets the retention times (in seconds)
for each spectrum. 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 represents the index of the
spectrum during acquisition/measurement (as reported in the mzML file).
-
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(): gets general spectrum metadata (annotation, also called
header). spectraData() returns a DataFrame. Note that this
method does by default not return m/z or intensity values.
-
spectraData<-: replaces the full spectra data of the Spectra
object with the one provided with value. The spectraData<- function
expects a DataFrame to be passed as value with the same number of rows
as there a spectra in object. Note that replacing values of
peaks variables is not supported with a non-empty processing queue, i.e.
if any filtering or data manipulations on the peaks data was performed.
In these cases applyProcessing() needs to be called first to apply all
cached data operations and empty the processing queue.
-
spectraNames(), spectraNames<-: gets or sets the spectra names.
-
spectraVariables(): returns a character vector with the
available spectra variables (columns, fields or attributes of each
spectrum) available in object. Note that spectraVariables() does not
list the peak variables ("mz", "intensity" and eventual additional
annotations for each MS peak). Peak variables are returned by
peaksVariables().
-
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, 0 is returned.
-
uniqueMsLevels(): get the unique MS levels available in object. This
function is supposed to be more efficient than unique(msLevel(object)).
Author(s)
Sebastian Gibb, Johannes Rainer, Laurent Gatto, Philippine Louail
See Also
-
addProcessing() for functions to analyze Spectra.
-
Spectra for a general description of the Spectra object.
Examples
## Create a Spectra from mzML files and use the `MsBackendMzR` on-disk
## backend.
sciex_file <- dir(system.file("sciex", package = "msdata"),
full.names = TRUE)
sciex <- Spectra(sciex_file, backend = MsBackendMzR())
sciex
## Get the number of spectra in the data set
length(sciex)
## Get the number of mass peaks per spectrum - limit to the first 6
lengths(sciex) |> head()
## Get the MS level for each spectrum - limit to the first 6 spectra
msLevel(sciex) |> head()
## Alternatively, we could also use $ to access a specific spectra variable.
## This could also be used to add additional spectra variables to the
## object (see further below).
sciex$msLevel |> head()
## Get the intensity and m/z values.
intensity(sciex)
mz(sciex)
## Convert a subset of the Spectra object to a long DataFrame.
asDataFrame(sciex, i = 1:3, spectraVars = c("rtime", "msLevel"))
## Create a Spectra providing a `DataFrame` containing the spectrum data.
spd <- DataFrame(msLevel = c(1L, 2L), rtime = c(1.1, 1.2))
spd$mz <- list(c(100, 103.2, 104.3, 106.5), c(45.6, 120.4, 190.2))
spd$intensity <- list(c(200, 400, 34.2, 17), c(12.3, 15.2, 6.8))
s <- Spectra(spd)
s
## List all available spectra variables (i.e. spectrum data and metadata).
spectraVariables(s)
## For all *core* spectrum variables accessor functions are available. These
## return NA if the variable was not set.
centroided(s)
dataStorage(s)
rtime(s)
precursorMz(s)
## The core spectra variables are:
coreSpectraVariables()
## Add an additional metadata column.
s$spectrum_id <- c("sp_1", "sp_2")
## List spectra variables, "spectrum_id" is now also listed
spectraVariables(s)
## Get the values for the new spectra variable
s$spectrum_id
## Extract specific spectra variables.
spectraData(s, columns = c("spectrum_id", "msLevel"))
## -------- PEAKS VARIABLES AND DATA --------
## Get the peak data (m/z and intensity values).
pks <- peaksData(s)
pks
pks[[1]]
pks[[2]]
## Note that we could get the same resulb by coercing the `Spectra` to
## a `list` or `SimpleList`:
as(s, "list")
as(s, "SimpleList")
## Or use `mz()` and `intensity()` to extract the m/z and intensity values
## separately
mz(s)
intensity(s)
## Some `MsBackend` classes provide support for arbitrary peaks variables
## (in addition to the mandatory `"mz"` and `"intensity"` values. Below
## we create a simple data frame with an additional peak variable `"pk_ann"`
## and create a `Spectra` with a `MsBackendMemory` for that data.
## Importantly the number of values (per spectrum) need to be the same
## for all peak variables.
tmp <- data.frame(msLevel = c(2L, 2L), rtime = c(123.2, 123.5))
tmp$mz <- list(c(103.1, 110.4, 303.1), c(343.2, 453.1))
tmp$intensity <- list(c(130.1, 543.1, 40), c(0.9, 0.45))
tmp$pk_ann <- list(c(NA_character_, "A", "P"), c("B", "P"))
## Create the Spectra. With parameter `peaksVariables` we can define
## the columns in `tmp` that contain peaks variables.
sps <- Spectra(tmp, source = MsBackendMemory(),
peaksVariables = c("mz", "intensity", "pk_ann"))
peaksVariables(sps)
## Extract just the m/z and intensity values
peaksData(sps)[[1L]]
## Extract the full peaks data
peaksData(sps, columns = peaksVariables(sps))[[1L]]
## Access just the pk_ann variable
sps$pk_ann
rformassspectrometry/Spectra documentation built on Sept. 27, 2024, 5:43 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| spectraData | R Documentation |
Accessing mass spectrometry data
Description
As detailed in the documentation of the Spectra class, a Spectra object
is a container for mass spectrometry (MS) data that includes both the mass
peaks data (or peaks data, generally m/z and intensity values) as well
as spectra metadata (so called spectra variables). Spectra variables
generally define one value per spectrum, while for peaks variables one value
per mass peak is defined and hence multiple values per spectrum (depending
on the number of mass peaks of a spectrum).
Data can be extracted from a Spectra object using dedicated accessor
functions or also using the $ operator. Depending on the backend class
used by the Spectra to represent the data, data can also be added or
replaced (again, using dedicated functions or using $<-).
Usage
asDataFrame(
object,
i = seq_along(object),
spectraVars = spectraVariables(object)
)
## S4 method for signature 'Spectra'
acquisitionNum(object)
## S4 method for signature 'Spectra'
centroided(object)
## S4 replacement method for signature 'Spectra'
centroided(object) <- value
## S4 method for signature 'Spectra'
collisionEnergy(object)
## S4 replacement method for signature 'Spectra'
collisionEnergy(object) <- value
coreSpectraVariables()
## S4 method for signature 'Spectra'
dataOrigin(object)
## S4 replacement method for signature 'Spectra'
dataOrigin(object) <- value
## S4 method for signature 'Spectra'
dataStorage(object)
## S4 method for signature 'Spectra'
intensity(object, f = processingChunkFactor(object), ...)
## S4 method for signature 'Spectra'
ionCount(object)
## S4 method for signature 'Spectra'
isCentroided(object, ...)
## S4 method for signature 'Spectra'
isEmpty(x)
## S4 method for signature 'Spectra'
isolationWindowLowerMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowLowerMz(object) <- value
## S4 method for signature 'Spectra'
isolationWindowTargetMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowTargetMz(object) <- value
## S4 method for signature 'Spectra'
isolationWindowUpperMz(object)
## S4 replacement method for signature 'Spectra'
isolationWindowUpperMz(object) <- value
## S4 method for signature 'Spectra'
length(x)
## S4 method for signature 'Spectra'
lengths(x, use.names = FALSE)
## S4 method for signature 'Spectra'
msLevel(object)
## S4 method for signature 'Spectra'
mz(object, f = processingChunkFactor(object), ...)
## S4 method for signature 'Spectra'
peaksData(
object,
columns = c("mz", "intensity"),
f = processingChunkFactor(object),
...,
BPPARAM = bpparam()
)
## S4 method for signature 'Spectra'
peaksVariables(object)
## S4 method for signature 'Spectra'
polarity(object)
## S4 replacement method for signature 'Spectra'
polarity(object) <- value
## S4 method for signature 'Spectra'
precScanNum(object)
## S4 method for signature 'Spectra'
precursorCharge(object)
## S4 method for signature 'Spectra'
precursorIntensity(object)
## S4 method for signature 'Spectra'
precursorMz(object)
## S4 method for signature 'Spectra'
rtime(object)
## S4 replacement method for signature 'Spectra'
rtime(object) <- value
## S4 method for signature 'Spectra'
scanIndex(object)
## S4 method for signature 'Spectra'
smoothed(object)
## S4 replacement method for signature 'Spectra'
smoothed(object) <- value
## S4 method for signature 'Spectra'
spectraData(object, columns = spectraVariables(object))
## S4 replacement method for signature 'Spectra'
spectraData(object) <- value
## S4 method for signature 'Spectra'
spectraNames(object)
## S4 replacement method for signature 'Spectra'
spectraNames(object) <- value
## S4 method for signature 'Spectra'
spectraVariables(object)
## S4 method for signature 'Spectra'
tic(object, initial = TRUE)
## S4 method for signature 'Spectra'
uniqueMsLevels(object, ...)
## S4 method for signature 'Spectra'
x$name
## S4 replacement method for signature 'Spectra'
x$name <- value
## S4 method for signature 'Spectra'
x[[i, j, ...]]
## S4 replacement method for signature 'Spectra'
x[[i, j, ...]] <- value
Arguments
object |
A |
i |
For |
spectraVars |
|
value |
A vector with values to replace the respective spectra variable. Needs to be of the correct data type for the spectra variable. |
f |
For |
... |
Additional arguments. |
x |
A |
use.names |
For |
columns |
For |
BPPARAM |
Parallel setup configuration. See |
initial |
For |
name |
For |
j |
For |
Spectra variables
A common set of core spectra variables are defined for Spectra. These
have a pre-defined data type and each Spectra will return a value for
these if requested. If no value for a spectra variable is defined, a missing
value (of the correct data type) is returned. The list of core spectra
variables and their respective data type is:
-
acquisitionNum
integer(1): the index of acquisition of a spectrum during an MS run. -
centroided
logical(1): whether the spectrum is in profile or centroid mode. -
collisionEnergy
numeric(1): collision energy used to create an MSn spectrum. -
dataOrigin
character(1): the origin of the spectrum's data, e.g. the mzML file from which it was read. -
dataStorage
character(1): the (current) storage location of the spectrum data. This value depends on the backend used to handle and provide the data. For an in-memory backend like theMsBackendDataFramethis will be"<memory>", for an on-disk backend such as theMsBackendHdf5Peaksit will be the name of the HDF5 file where the spectrum's peak data is stored. -
isolationWindowLowerMz
numeric(1): lower m/z for the isolation window in which the (MSn) spectrum was measured. -
isolationWindowTargetMz
numeric(1): the target m/z for the isolation window in which the (MSn) spectrum was measured. -
isolationWindowUpperMz
numeric(1): upper m/z for the isolation window in which the (MSn) spectrum was measured. -
msLevel
integer(1): the MS level of the spectrum. -
polarity
integer(1): the polarity of the spectrum (0and1representing negative and positive polarity, respectively). -
precScanNum
integer(1): the scan (acquisition) number of the precursor for an MSn spectrum. -
precursorCharge
integer(1): the charge of the precursor of an MSn spectrum. -
precursorIntensity
numeric(1): the intensity of the precursor of an MSn spectrum. -
precursorMz
numeric(1): the m/z of the precursor of an MSn spectrum. -
rtime
numeric(1): the retention time of a spectrum. -
scanIndex
integer(1): the index of a spectrum within a (raw) file. -
smoothed
logical(1): whether the spectrum was smoothed.
For each of these spectra variable a dedicated accessor function is defined
(such as msLevel() or rtime()) that allows to extract the values of
that spectra variable for all spectra in a Spectra object. Also,
replacement functions are defined, but not all backends might support
replacing values for spectra variables. As described above, additional
spectra variables can be defined or added. The spectraVariables() function
can be used to
Values for multiple spectra variables, or all spectra vartiables* can be
extracted with the spectraData() function.
Peaks variables
Spectra also provide mass peak data with the m/z and intensity values
being the core peaks variables:
-
intensity
numeric: intensity values for the spectrum's peaks. -
mz
numeric: the m/z values for the spectrum's peaks.
Values for these can be extracted with the mz() and intensity()
functions, or the peaksData() function. The former functions return a
NumericList with the respective values, while the latter returns a List
with numeric two-column matrices. The list of peaks matrices can also
be extracted using as(x, "list") or as(x, "SimpleList") with x being
a Spectra object.
Some Spectra/backends provide also values for additional peaks variables.
The set of available peaks variables can be extracted with the
peaksVariables() function.
Functions to access MS data
The set of available functions to extract data from, or set data in, a
Spectra object are (in alphabetical order) listed below. Note that there
are also other functions to extract information from a Spectra object
documented in addProcessing().
-
$,$<-: gets (or sets) a spectra variable for all spectra inobject. See examples for details. Note that replacing values of a peaks variable is not supported with a non-empty processing queue, i.e. if any filtering or data manipulations on the peaks data was performed. In these casesapplyProcessing()needs to be called first to apply all cached data operations. -
[[,[[<-: access or set/add a single spectrum variable (column) in the backend. -
acquisitionNum(): returns the acquisition number of each spectrum. Returns anintegerof length equal to the number of spectra (withNA_integer_if not available). -
asDataFrame(): converts theSpectrato aDataFrame(in long format) contining all data. Returns aDataFrame. -
centroided(),centroided<-: gets or sets the centroiding information of the spectra.centroided()returns alogicalvector of length equal to the number of spectra withTRUEif a spectrum is centroided,FALSEif it is in profile mode andNAif it is undefined. See alsoisCentroided()for estimating from the spectrum data whether the spectrum is centroided.valueforcentroided<-is either a singlelogicalor alogicalof length equal to the number of spectra inobject. -
collisionEnergy(),collisionEnergy<-: gets or sets the collision energy for all spectra inobject.collisionEnergy()returns anumericwith length equal to the number of spectra (NA_real_if not present/defined),collisionEnergy<-takes anumericof length equal to the number of spectra inobject. -
coreSpectraVariables(): returns the core spectra variables along with their expected data type. -
dataOrigin(),dataOrigin<-: gets or sets the data origin for each spectrum.dataOrigin()returns acharactervector (same length thanobject) with the origin of the spectra.dataOrigin<-expects acharactervector (same length thanobject) with the replacement values for the data origin of each spectrum. -
dataStorage(): returns acharactervector (same length thanobject) with the data storage location of each spectrum. -
intensity(): gets the intensity values from the spectra. Returns aNumericList()ofnumericvectors (intensity values for each spectrum). The length of the list is equal to the number ofspectrainobject. -
ionCount(): returns anumericwith the sum of intensities for each spectrum. If the spectrum is empty (seeisEmpty()),NA_real_is returned. -
isCentroided(): a heuristic approach assessing if the spectra inobjectare 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. (SeeSpectra:::.isCentroided()for the code.) -
isEmpty(): checks whether a spectrum inobjectis empty (i.e. does not contain any peaks). Returns alogicalvector 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. -
length(): gets the number of spectra in the object. -
lengths(): gets the number of peaks (m/z-intensity values) per spectrum. Returns anintegervector (length equal to the number of spectra). For empty spectra,0is returned. -
msLevel(): gets the spectra's MS level. Returns an integer vector (names being spectrum names, length equal to the number of spectra) with the MS level for each spectrum. -
mz(): gets the mass-to-charge ratios (m/z) from the spectra. Returns aNumericList()or length equal to the number of spectra, each element anumericvector with the m/z values of one spectrum. -
peaksData(): gets the peaks data for all spectra inobject. Peaks data consist of the m/z and intensity values as well as possible additional annotations (variables) of all peaks of each spectrum. The function returns aSimpleList()of two dimensional arrays (eithermatrixordata.frame), with each array providing the values for the requested peak variables (by default"mz"and"intensity"). Optional parametercolumnsis passed to the backend'speaksData()function to allow the selection of specific (or additional) peaks variables (columns) that should be extracted (if available). Importantly, it is not guaranteed that each backend supports this parameter (while each backend must support extraction of"mz"and"intensity"columns). Parametercolumnsdefaults toc("mz", "intensity")but any value returned bypeaksVariables(object)is supported. Note also that it is possible to extract the peak data withas(x, "list")andas(x, "SimpleList")as alistandSimpleList, respectively. Note however that, in contrast topeaksData(),as()does not support the parametercolumns. -
peaksVariables(): lists the available variables for mass peaks provided by the backend. Default peak variables are"mz"and"intensity"(which all backends need to support and provide), but some backends might provide additional variables. These variables correspond to the column names of the peak data array returned bypeaksData(). -
polarity(),polarity<-: gets or sets the polarity for each spectrum.polarity()returns anintegervector (length equal to the number of spectra), with0and1representing negative and positive polarities, respectively.polarity<-expects anintegervector of length 1 or equal to the number of spectra. -
precursorCharge(),precursorIntensity(),precursorMz(),precScanNum(),precAcquisitionNum(): gets the charge (integer), intensity (numeric), m/z (numeric), scan index (integer) and acquisition number (interger) of the precursor for MS level > 2 spectra from the object. Returns a vector of length equal to the number of spectra inobject.NAare reported for MS1 spectra of if no precursor information is available. -
rtime(),rtime<-: gets or sets the retention times (in seconds) for each spectrum.rtime()returns anumericvector (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 anintegervector 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 theacquisitionNumof the spectrum which represents the index of the spectrum during acquisition/measurement (as reported in the mzML file). -
smoothed(),smoothed<-: gets or sets whether a spectrum is smoothed.smoothed()returns alogicalvector of length equal to the number of spectra.smoothed<-takes alogicalvector of length 1 or equal to the number of spectra inobject. -
spectraData(): gets general spectrum metadata (annotation, also called header).spectraData()returns aDataFrame. Note that this method does by default not return m/z or intensity values. -
spectraData<-: replaces the full spectra data of theSpectraobject with the one provided withvalue. ThespectraData<-function expects aDataFrameto be passed as value with the same number of rows as there a spectra inobject. Note that replacing values of peaks variables is not supported with a non-empty processing queue, i.e. if any filtering or data manipulations on the peaks data was performed. In these casesapplyProcessing()needs to be called first to apply all cached data operations and empty the processing queue. -
spectraNames(),spectraNames<-: gets or sets the spectra names. -
spectraVariables(): returns acharactervector with the available spectra variables (columns, fields or attributes of each spectrum) available inobject. Note thatspectraVariables()does not list the peak variables ("mz","intensity"and eventual additional annotations for each MS peak). Peak variables are returned bypeaksVariables(). -
tic(): gets the total ion current/count (sum of signal of a spectrum) for all spectra inobject. By default, the value reported in the original raw data file is returned. For an empty spectrum,0is returned. -
uniqueMsLevels(): get the unique MS levels available inobject. This function is supposed to be more efficient thanunique(msLevel(object)).
Author(s)
Sebastian Gibb, Johannes Rainer, Laurent Gatto, Philippine Louail
See Also
-
addProcessing()for functions to analyzeSpectra. -
Spectra for a general description of the
Spectraobject.
Examples
## Create a Spectra from mzML files and use the `MsBackendMzR` on-disk
## backend.
sciex_file <- dir(system.file("sciex", package = "msdata"),
full.names = TRUE)
sciex <- Spectra(sciex_file, backend = MsBackendMzR())
sciex
## Get the number of spectra in the data set
length(sciex)
## Get the number of mass peaks per spectrum - limit to the first 6
lengths(sciex) |> head()
## Get the MS level for each spectrum - limit to the first 6 spectra
msLevel(sciex) |> head()
## Alternatively, we could also use $ to access a specific spectra variable.
## This could also be used to add additional spectra variables to the
## object (see further below).
sciex$msLevel |> head()
## Get the intensity and m/z values.
intensity(sciex)
mz(sciex)
## Convert a subset of the Spectra object to a long DataFrame.
asDataFrame(sciex, i = 1:3, spectraVars = c("rtime", "msLevel"))
## Create a Spectra providing a `DataFrame` containing the spectrum data.
spd <- DataFrame(msLevel = c(1L, 2L), rtime = c(1.1, 1.2))
spd$mz <- list(c(100, 103.2, 104.3, 106.5), c(45.6, 120.4, 190.2))
spd$intensity <- list(c(200, 400, 34.2, 17), c(12.3, 15.2, 6.8))
s <- Spectra(spd)
s
## List all available spectra variables (i.e. spectrum data and metadata).
spectraVariables(s)
## For all *core* spectrum variables accessor functions are available. These
## return NA if the variable was not set.
centroided(s)
dataStorage(s)
rtime(s)
precursorMz(s)
## The core spectra variables are:
coreSpectraVariables()
## Add an additional metadata column.
s$spectrum_id <- c("sp_1", "sp_2")
## List spectra variables, "spectrum_id" is now also listed
spectraVariables(s)
## Get the values for the new spectra variable
s$spectrum_id
## Extract specific spectra variables.
spectraData(s, columns = c("spectrum_id", "msLevel"))
## -------- PEAKS VARIABLES AND DATA --------
## Get the peak data (m/z and intensity values).
pks <- peaksData(s)
pks
pks[[1]]
pks[[2]]
## Note that we could get the same resulb by coercing the `Spectra` to
## a `list` or `SimpleList`:
as(s, "list")
as(s, "SimpleList")
## Or use `mz()` and `intensity()` to extract the m/z and intensity values
## separately
mz(s)
intensity(s)
## Some `MsBackend` classes provide support for arbitrary peaks variables
## (in addition to the mandatory `"mz"` and `"intensity"` values. Below
## we create a simple data frame with an additional peak variable `"pk_ann"`
## and create a `Spectra` with a `MsBackendMemory` for that data.
## Importantly the number of values (per spectrum) need to be the same
## for all peak variables.
tmp <- data.frame(msLevel = c(2L, 2L), rtime = c(123.2, 123.5))
tmp$mz <- list(c(103.1, 110.4, 303.1), c(343.2, 453.1))
tmp$intensity <- list(c(130.1, 543.1, 40), c(0.9, 0.45))
tmp$pk_ann <- list(c(NA_character_, "A", "P"), c("B", "P"))
## Create the Spectra. With parameter `peaksVariables` we can define
## the columns in `tmp` that contain peaks variables.
sps <- Spectra(tmp, source = MsBackendMemory(),
peaksVariables = c("mz", "intensity", "pk_ann"))
peaksVariables(sps)
## Extract just the m/z and intensity values
peaksData(sps)[[1L]]
## Extract the full peaks data
peaksData(sps, columns = peaksVariables(sps))[[1L]]
## Access just the pk_ann variable
sps$pk_ann
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.