BiocStyle::markdown()
Load required packages and functions.
library("MSnbase") library("MSnbaseBoxCar") library("ggplot2")
Read a small dataset composed of 16 MS1 spectra as an MSnExp
:
f <- dir(system.file("extdata", package = "MSnbaseBoxCar"), pattern = "boxcar.mzML", full.names = TRUE) basename(f) x <- readMSData(f, mode = "onDisk") x
Define boxcar groups based on the filterString
metadata variable:
full scans are encoded as "FTMS + p NSI Full ms
[375.0000-1800.0000]"
while their respective Boxcar scans reflect the
provide adjacent m/z segments "FTMS + p NSI SIM msx ms
[299.0000-1701.0000, 299.0000-351.0000, ...]"
fData(x)$filterString[1:4]
The bc_groups
function identifies full (noted NA
) and BoxCar
spectra and groups the latter:
x <- bc_groups(x) fData(x)$bc_groups
The next filter BoxCar spectra, as defined above.
xbc <- filterBoxCar(x) fData(xbc)$bc_groups
bc_plot(xbc[1:3]) + xlim(440, 510)
Remove any peaks outside of the BoxCar segments.
xbc <- bc_zero_out_box(xbc, offset = 0.5) xbc
bc_plot(xbc[1:3]) + xlim(440, 510)
Combine BoxCar spectra to reconstitute the full scan and coerce result
back to an MSnExp
object containing 4 spectra.
res <- combineSpectra(xbc, fcol = "bc_groups", method = boxcarCombine) res
plot(res[[1]])
The above steps can also be piped into a single command.
library("magrittr") res <- x %>% bc_groups() %>% filterBoxCar() %>% bc_zero_out_box(offset = 0.5) %>% combineSpectra(fcol = "groups", method = boxcarCombine)
The processed data can also be written to a new mzML file.
writeMSData(res, "boxcar_processed.mzML")
MSnbase
- an R/Bioconductor package for isobaric tagged mass
spectrometry data visualization, processing and
quantitation.MSnbase
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