The r BiocStyle::Biocpkg("mzR")
package aims at providing a common, low-level
interface to several mass spectrometry data formats, namely mzData
[@Orchard2007], mzXML
[@Pedrioli2004], mzML
[@Martens2010] for raw
data, and mzIdentML
[@Jones2012], somewhat similar to the
Bioconductor package affyio for affymetrix raw data. No processing is
done in r BiocStyle::Biocpkg("mzR")
, which is left to packages such as r
BiocStyle::Biocpkg("xcms")
[@Smith:2006, Tautenhahn:2008] or
r BiocStyle::Biocpkg("MSnbase")
[@Gatto:2012]. These packages also provide more
convenient, high-level interfaces to raw and identification. data
Most importantly, access to the data should be fast and memory efficient. This is made possible by allowing on-disk random file access, i.e. retrieving specific data of interest without having to sequentially browser the full content nor loading the entire data into memory.
The actual work of reading and parsing the data files is handled by
the included C/C++ libraries or backends. The mzRramp
RAMP parser,
written at the Institute for Systems Biology (ISB) is a fast and
lightweight parser in pure C. Later, it gained support for the
mzData
format. The C++ reference implementation for the mzML
is
the proteowizard library [@Kessner08] (pwiz in short), which in turn
makes use of the boost C++ (http://www.boost.org/) library. RAMP is
able to access mzML
files by calling pwiz methods. More recently,
the proteowizard (http://proteowizard.sourceforge.net/)
[@Chambers2012] has been fully integrated using the mzRpwiz
backend
for raw data, and is not the default option. The mzRnetCDF
backend
provides support to CDF
-based formats. Finally, the mzRident
backend is available to access identification data (mzIdentML
)
through pwiz.
The r BiocStyle::Biocpkg("mzR")
package is in essence a collection of wrappers
to the C++ code, and benefits from the C++ interface provided through
the Rcpp package [@Rcpp11].
IMPORTANT New developers that need to access and manipulate raw
mass spectrometry data are advised against using this infrastucture
directly. They are invited to use the corresponding MSnExp
(with on
disk mode) from ther BiocStyle::Biocpkg("MSnbase")
package instead. The
latter supports reading multiple files at once and offers access to
the spectra data (m/z and intensity) as well as all the spectra
metadata using a coherent interface. The MSnbase infrastructure itself
used the low level classes in mzR, thus offering fast and efficient
access.
All the mass spectrometry file formats are organized similarly, where a set of metadata nodes about the run is followed by a list of spectra with the actual masses and intensities. In addition, each of these spectra has its own set of metadata, such as the retention time and acquisition parameters.
Access to the spectral data is done via the peaks
function. The
return value is a list of two-column mass-to-charge and intensity
matrices or a single matrix if one spectrum is queried.
Access to the chromatogram(s) is done using the chromatogram
(or
chromatograms
) function, that return one (or a list of)
data.frames. See ?chromatogram
for details. This functionality is
only available with the pwiz
backend.
The main access to identification result is done via psms
, score
and modifications
. psms
and score
will return the detailed
information on each psm and scores. modifications
will return the
details on each modification found in peptide.
Run metadata is available via several functions such as
instrumentInfo()
or runInfo()
. The individual fields can be
accessed via e.g. detector()
etc.
Spectrum metadata is available via header()
, which will return a
list (for single scans) or a dataframe with information such as the
basePeakMZ
, peaksCount
, ... or, for higher-order MS the msLevel
and precursor information.
Identification metadatais available via mzidInfo()
, which will
return a list with information such as the software
,
ModificationSearched
, enzymes
, SpectraSource
and other
information for this identification result.
The availability of this metadata can not always be guaranteed, and depends on the MS software which converted the data.
mzXML
/mzML
/mzData
filesA short example sequence to read data from a mass spectrometer. First open the file.
library(mzR) library(msdata) mzxml <- system.file("threonine/threonine_i2_e35_pH_tree.mzXML", package = "msdata") aa <- openMSfile(mzxml)
We can obtain different kind of header information.
runInfo(aa) instrumentInfo(aa) header(aa,1)
Read a single spectrum from the file.
pl <- peaks(aa,10) peaksCount(aa,10) head(pl) plot(pl[,1], pl[,2], type="h", lwd=1)
One should always close the file when not needed any more. This will release the memory of cached content.
close(aa)
mzIdentML
filesYou can use openIDfile
to read a mzIdentML
file (version 1.1),
which use the pwiz backend.
library(mzR) library(msdata) file <- system.file("mzid", "Tandem.mzid.gz", package="msdata") x <- openIDfile(file)
mzidInfo
function will return general information about this
identification result.
mzidInfo(x)
psms
will return the detailed information on each
peptide-spectrum-match, include spectrumID
, chargeState
,
sequence
. modNum
and others.
p <- psms(x) colnames(p)
The modifications information can be accessed using modifications
,
which will return the spectrumID
, sequence
, name
, mass
and
location
.
m <- modifications(x) head(m)
Since different software will use different scoring function, we
provide a score
to extract the scores for each psm. It will return a
data.frame with different columns depending on software generating
this file.
scr <- score(x) colnames(scr)
Other file formats provided by HUPO, such as mzQuantML
for
quantitative data [@Walzer:2013] are also possible in the future.
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