BiocStyle::markdown()

Package: r Biocpkg("MsBackendMgf")
Authors: r packageDescription("MsBackendMgf")[["Author"]]
Last modified: r file.info("MsBackendMgf.Rmd")$mtime
Compiled: r date()

library(Spectra)
library(BiocStyle)

Introduction

The r Biocpkg("Spectra") package provides a central infrastructure for the handling of Mass Spectrometry (MS) data. The package supports interchangeable use of different backends to import MS data from a variety of sources (such as mzML files). The r Biocpkg("MsBackendMgf") package allows the import of MS/MS data from mgf (Mascot Generic Format) files. This vignette illustrates the usage of the MsBackendMgf package.

Installation

To install this package, start R and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MsBackendMgf")

This will install this package and all eventually missing dependencies.

Importing MS/MS data from mgf files

Mgf files store one to multiple spectra, typically centroided and of MS level 2. In our short example below, we load 2 mgf files which are provided with this package. Below we first load all required packages and define the paths to the mgf files.

library(Spectra)
library(MsBackendMgf)

fls <- dir(system.file("extdata", package = "MsBackendMgf"),
           full.names = TRUE, pattern = "mgf$")
fls

MS data can be accessed and analyzed through Spectra objects. Below we create a Spectra with the data from these mgf files. To this end we provide the file names and specify to use a MsBackendMgf() backend as source to enable data import.

sps <- Spectra(fls, source = MsBackendMgf())

With that we have now full access to all imported spectra variables that we list below.

spectraVariables(sps)

Besides default spectra variables, such as msLevel, rtime, precursorMz, we also have additional spectra variables such as the TITLE of each spectrum in the mgf file.

sps$rtime
sps$TITLE

By default, fields in the mgf file are mapped to spectra variable names using the mapping returned by the spectraVariableMapping function:

spectraVariableMapping(MsBackendMgf())

The names of this character vector are the spectra variable names (such as "rtime") and the field in the mgf file that contains that information are the values (such as "RTINSECONDS"). Note that it is also possible to overwrite this mapping (e.g. for certain mgf dialects) or to add additional mappings. Below we add the mapping of the mgf field "TITLE" to a spectra variable called "spectrumName".

map <- c(spectrumName = "TITLE", spectraVariableMapping(MsBackendMgf()))
map

We can then pass this mapping to the backendInitialize method, or the Spectra constructor.

sps <- Spectra(fls, source = MsBackendMgf(), mapping = map)

We can now access the spectrum's title with the newly created spectra variable "spectrumName":

sps$spectrumName

In addition we can also access the m/z and intensity values of each spectrum.

mz(sps)
intensity(sps)

The MsBackendMgf backend allows also to export data in mgf format. Below we export the data to a temporary file. We hence call the export function on our Spectra object specifying backend = MsBackendMgf() to use this backend for the export of the data. Note that we use again our custom mapping of variables such that the spectra variable "spectrumName" will be exported as the spectrums' title.

fl <- tempfile()
export(sps, backend = MsBackendMgf(), file = fl, mapping = map)

We next read the first lines from the exported file to verify that the title was exported properly.

readLines(fl)[1:12]

Note that the MsBackendMgf exports all spectra variables as fields in the mgf file. To illustrate this we add below a new spectra variable to the object and export the data.

sps$new_variable <- "A"
export(sps, backend = MsBackendMgf(), file = fl)
readLines(fl)[1:12]

We can see that also our newly defined variable was exported. Also, because we did not provide our custom variable mapping this time, the variable "spectrumName" was not used as the spectrum's title.

Sometimes it might be required to not export all spectra variables since some exported fields might not be recognized/supported by external tools. Using the selectSpectraVariables function we can reduce our Spectra object to export to contain only relevant spectra variables. Below we restrict the data to only m/z, intensity, retention time, acquisition number, precursor m/z and precursor charge and export these to an mgf file. Also, some external tools don't support the "TITLE" field in the MGF file. To disable export of the spectrum ID/title exportTitle = FALSE can be used.

sps_ex <- selectSpectraVariables(sps, c("mz", "intensity", "rtime",
                                        "acquisitionNum", "precursorMz",
                                        "precursorCharge"))
export(sps_ex, backend = MsBackendMgf(), file = fl, exportTitle = FALSE)
readLines(fl)[1:12]

Parallel processing

The MsBackendMgf package supports parallel processing for data import. Parallel processing can be enabled by providing the parallel processing setup to the backendInitialize function (or the readMgf function) with the BPPARAM parameter. By default (with BPPARAM = SerialParam()) parallel processing is disabled. If enabled, and data import is performed on a single file, the extraction of spectra information on the imported MGF file is performed in parallel. If data is to be imported from multiple files, the import is performed in parallel on a per-file basis (i.e. in parallel from the different files). Generally, the performance gain through parallel processing is only moderate and it is only suggested if a large number of files need to be processed, or if the MGF file is very large (e.g. containing over 100,000 spectra).

Session information

sessionInfo()


rformassspectrometry/MsBackendMgf documentation built on Jan. 17, 2025, 9:55 a.m.