May Institute 2020
7 May 2020
1 Introduction
These are the live notes from my talk at the (remote) May Institute 2020. I will present material from
MSnbase, efficient and elegant R-based processing and visualisation of raw mass spectrometry data. Laurent Gatto, Sebastian Gibb, Johannes Rainer bioRxiv 2020.04.29.067868; doi: https://doi.org/10.1101/2020.04.29.067868
See also
The
MSnbasehome page: http://lgatto.github.io/MSnbase/MSnbase - an R/Bioconductor package for isobaric tagged mass spectrometry data visualisation, processing and quantitation. Gatto L. and Lilley K.S. Bioinformatics, 28(2), 288-289, 2012.
Acknowledgement: Johannes Rainer and Sebastian Gibb
Questions about your data/analyses/issues:
- Bioconductor support site: https://support.bioconductor.org/
- MSnbase issues on GitHub: https://github.com/lgatto/MSnbase
2 On-disk backend
f <- msdata::proteomics(pattern = "201412", full.names = TRUE)
basename(f)## [1] "TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz"library(MSnbase)
library(magrittr)Reading on-disk is faster. See Figure 1a in the pre-print.
system.time(x_mem <- readMSData(f, mode = "inMemory"))## user system elapsed
## 59.396 0.432 59.520system.time(x_dsk <- readMSData(f, mode = "onDisk"))## user system elapsed
## 11.132 0.336 11.201The MSnExp class
x_dsk## MSn experiment data ("OnDiskMSnExp")
## Object size in memory: 3.31 Mb
## - - - Spectra data - - -
## MS level(s): 1 2
## Number of spectra: 7534
## MSn retention times: 0:0 - 60:2 minutes
## - - - Processing information - - -
## Data loaded [Thu May 7 19:51:53 2020]
## MSnbase version: 2.14.0
## - - - Meta data - - -
## phenoData
## rowNames:
## TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz
## varLabels: sampleNames
## varMetadata: labelDescription
## Loaded from:
## TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz
## protocolData: none
## featureData
## featureNames: F1.S0001 F1.S0002 ... F1.S7534 (7534 total)
## fvarLabels: fileIdx spIdx ... spectrum (35 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'fData(x_dsk)## fileIdx spIdx smoothed seqNum acquisitionNum msLevel polarity
## F1.S0001 1 1 NA 1 1 1 1
## F1.S0002 1 2 NA 2 2 1 1
## F1.S0003 1 3 NA 3 3 1 1
## F1.S0004 1 4 NA 4 4 1 1
## F1.S0005 1 5 NA 5 5 1 1
## F1.S0006 1 6 NA 6 6 1 1
## F1.S0007 1 7 NA 7 7 1 1
## F1.S0008 1 8 NA 8 8 1 1
## F1.S0009 1 9 NA 9 9 1 1
## F1.S0010 1 10 NA 10 10 1 1
## F1.S0011 1 11 NA 11 11 1 1
## F1.S0012 1 12 NA 12 12 1 1
## F1.S0013 1 13 NA 13 13 1 1
## F1.S0014 1 14 NA 14 14 1 1
## originalPeaksCount totIonCurrent retentionTime basePeakMZ
## F1.S0001 25800 9187505 0.4584 445.12
## F1.S0002 25934 9118685 0.9725 445.12
## F1.S0003 26148 9247653 1.8524 445.12
## F1.S0004 26330 9195261 2.7424 445.12
## F1.S0005 26463 9202081 3.6124 445.12
## F1.S0006 25580 9451720 4.4925 445.12
## F1.S0007 25191 9370178 5.3825 445.12
## F1.S0008 26957 9297793 6.2525 445.12
## F1.S0009 26608 9543710 7.1324 445.12
## F1.S0010 27062 9437697 8.0324 445.12
## F1.S0011 25763 9244707 8.8925 445.12
## F1.S0012 25577 9294566 9.7724 445.12
## F1.S0013 26282 9231183 10.6624 445.12
## F1.S0014 24474 9163494 11.5324 445.12
## basePeakIntensity collisionEnergy ionisationEnergy lowMZ highMZ
## F1.S0001 984171.2 NA 0 399.9987 2008.454
## F1.S0002 989260.4 NA 0 399.9985 2008.453
## F1.S0003 997621.7 NA 0 399.9983 2008.453
## F1.S0004 988598.2 NA 0 399.9981 2008.451
## F1.S0005 971233.9 NA 0 399.9983 2008.452
## F1.S0006 1000968.4 NA 0 399.9981 2008.451
## F1.S0007 1004060.4 NA 0 399.9980 2008.451
## F1.S0008 985961.2 NA 0 399.9980 2008.451
## F1.S0009 1012269.5 NA 0 399.9980 2008.451
## F1.S0010 983832.0 NA 0 399.9980 2008.451
## F1.S0011 976695.8 NA 0 399.9978 2008.450
## F1.S0012 994047.6 NA 0 399.9979 2008.450
## F1.S0013 971733.5 NA 0 399.9978 2008.450
## F1.S0014 987855.7 NA 0 399.9977 2008.449
## precursorScanNum precursorMZ precursorCharge precursorIntensity
## F1.S0001 NA NA NA NA
## F1.S0002 NA NA NA NA
## F1.S0003 NA NA NA NA
## F1.S0004 NA NA NA NA
## F1.S0005 NA NA NA NA
## F1.S0006 NA NA NA NA
## F1.S0007 NA NA NA NA
## F1.S0008 NA NA NA NA
## F1.S0009 NA NA NA NA
## F1.S0010 NA NA NA NA
## F1.S0011 NA NA NA NA
## F1.S0012 NA NA NA NA
## F1.S0013 NA NA NA NA
## F1.S0014 NA NA NA NA
## mergedScan mergedResultScanNum mergedResultStartScanNum
## F1.S0001 NA NA NA
## F1.S0002 NA NA NA
## F1.S0003 NA NA NA
## F1.S0004 NA NA NA
## F1.S0005 NA NA NA
## F1.S0006 NA NA NA
## F1.S0007 NA NA NA
## F1.S0008 NA NA NA
## F1.S0009 NA NA NA
## F1.S0010 NA NA NA
## F1.S0011 NA NA NA
## F1.S0012 NA NA NA
## F1.S0013 NA NA NA
## F1.S0014 NA NA NA
## mergedResultEndScanNum injectionTime
## F1.S0001 NA 50.38262
## F1.S0002 NA 51.13650
## F1.S0003 NA 50.36058
## F1.S0004 NA 51.23796
## F1.S0005 NA 50.87993
## F1.S0006 NA 50.30515
## F1.S0007 NA 50.08440
## F1.S0008 NA 49.81701
## F1.S0009 NA 51.12255
## F1.S0010 NA 50.92492
## F1.S0011 NA 51.28786
## F1.S0012 NA 48.79818
## F1.S0013 NA 50.32028
## F1.S0014 NA 50.93900
## filterString
## F1.S0001 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0002 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0003 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0004 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0005 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0006 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0007 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0008 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0009 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0010 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0011 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0012 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0013 FTMS + p NSI Full ms [400.00-2000.00]
## F1.S0014 FTMS + p NSI Full ms [400.00-2000.00]
## spectrumId centroided
## F1.S0001 controllerType=0 controllerNumber=1 scan=1 FALSE
## F1.S0002 controllerType=0 controllerNumber=1 scan=2 FALSE
## F1.S0003 controllerType=0 controllerNumber=1 scan=3 FALSE
## F1.S0004 controllerType=0 controllerNumber=1 scan=4 FALSE
## F1.S0005 controllerType=0 controllerNumber=1 scan=5 FALSE
## F1.S0006 controllerType=0 controllerNumber=1 scan=6 FALSE
## F1.S0007 controllerType=0 controllerNumber=1 scan=7 FALSE
## F1.S0008 controllerType=0 controllerNumber=1 scan=8 FALSE
## F1.S0009 controllerType=0 controllerNumber=1 scan=9 FALSE
## F1.S0010 controllerType=0 controllerNumber=1 scan=10 FALSE
## F1.S0011 controllerType=0 controllerNumber=1 scan=11 FALSE
## F1.S0012 controllerType=0 controllerNumber=1 scan=12 FALSE
## F1.S0013 controllerType=0 controllerNumber=1 scan=13 FALSE
## F1.S0014 controllerType=0 controllerNumber=1 scan=14 FALSE
## ionMobilityDriftTime isolationWindowTargetMZ
## F1.S0001 NA NA
## F1.S0002 NA NA
## F1.S0003 NA NA
## F1.S0004 NA NA
## F1.S0005 NA NA
## F1.S0006 NA NA
## F1.S0007 NA NA
## F1.S0008 NA NA
## F1.S0009 NA NA
## F1.S0010 NA NA
## F1.S0011 NA NA
## F1.S0012 NA NA
## F1.S0013 NA NA
## F1.S0014 NA NA
## isolationWindowLowerOffset isolationWindowUpperOffset
## F1.S0001 NA NA
## F1.S0002 NA NA
## F1.S0003 NA NA
## F1.S0004 NA NA
## F1.S0005 NA NA
## F1.S0006 NA NA
## F1.S0007 NA NA
## F1.S0008 NA NA
## F1.S0009 NA NA
## F1.S0010 NA NA
## F1.S0011 NA NA
## F1.S0012 NA NA
## F1.S0013 NA NA
## F1.S0014 NA NA
## scanWindowLowerLimit scanWindowUpperLimit spectrum
## F1.S0001 400 2000 1
## F1.S0002 400 2000 2
## F1.S0003 400 2000 3
## F1.S0004 400 2000 4
## F1.S0005 400 2000 5
## F1.S0006 400 2000 6
## F1.S0007 400 2000 7
## F1.S0008 400 2000 8
## F1.S0009 400 2000 9
## F1.S0010 400 2000 10
## F1.S0011 400 2000 11
## F1.S0012 400 2000 12
## F1.S0013 400 2000 13
## F1.S0014 400 2000 14
## [ reached 'max' / getOption("max.print") -- omitted 7520 rows ]fvarLabels(x_dsk)## [1] "fileIdx" "spIdx"
## [3] "smoothed" "seqNum"
## [5] "acquisitionNum" "msLevel"
## [7] "polarity" "originalPeaksCount"
## [9] "totIonCurrent" "retentionTime"
## [11] "basePeakMZ" "basePeakIntensity"
## [13] "collisionEnergy" "ionisationEnergy"
## [15] "lowMZ" "highMZ"
## [17] "precursorScanNum" "precursorMZ"
## [19] "precursorCharge" "precursorIntensity"
## [21] "mergedScan" "mergedResultScanNum"
## [23] "mergedResultStartScanNum" "mergedResultEndScanNum"
## [25] "injectionTime" "filterString"
## [27] "spectrumId" "centroided"
## [29] "ionMobilityDriftTime" "isolationWindowTargetMZ"
## [31] "isolationWindowLowerOffset" "isolationWindowUpperOffset"
## [33] "scanWindowLowerLimit" "scanWindowUpperLimit"
## [35] "spectrum"sp <- x_dsk[[1]]
sp## Object of class "Spectrum1"
## Retention time: 0:0
## MSn level: 1
## Total ion count: 25800
## Polarity: 1head(mz(sp))## [1] 399.9987 400.0002 400.0017 400.0032 400.2951 400.2966head(intensity(sp))## [1] 0 0 0 0 0 0plot(sp)
The on-disk data contains all spectra
length(x_dsk)## [1] 7534length(x_mem)## [1] 6103table(msLevel(x_dsk))##
## 1 2
## 1431 6103On-disk data uses less RAM. See Figure 1b in the pre-print.
pryr::object_size(x_mem)## Registered S3 method overwritten by 'pryr':
## method from
## print.bytes Rcpp## 33.2 MBpryr::object_size(x_dsk)## 3.46 MBx_dsk2 <- filterMsLevel(x_dsk, 2L)Access to raw data is faster when already in RAM. See Figure 1d in pre-print.
system.time(x_dsk[[1]])## user system elapsed
## 1.856 0.118 1.892system.time(x_mem[[1]])## user system elapsed
## 0.000 0.000 0.001Filtering: retention time between 1000 and 3000 seconds
chr1 <- chromatogram(x_dsk)
chr1## Chromatograms with 1 row and 1 column
## TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz
## <Chromatogram>
## [1,] length: 1431
## phenoData with 1 variables
## featureData with 1 variablesplot(chr1)
Filtering: keep TMT6 MZ range
plot(x_dsk2[[1227]], reporters = TMT6, full = TRUE)
TMT6## Object of class "ReporterIons"
## TMT6: '6-plex TMT tags' with 6 reporter ions
## - [TMT6.126] 126.1277 +/- 0.05 (red)
## - [TMT6.127] 127.1311 +/- 0.05 (purple)
## - [TMT6.128] 128.1344 +/- 0.05 (blue)
## - [TMT6.129] 129.1378 +/- 0.05 (steelblue)
## - [TMT6.130] 130.1411 +/- 0.05 (green)
## - [TMT6.131] 131.1382 +/- 0.05 (yellow)range(mz(TMT6))## [1] 126.1277 131.1382Filtering: keep 50% spectra with highest precursor ion intensity
median(precursorIntensity(x_dsk2))## [1] 11364716filter_ms <- function(x) {
x <- x %>%
filterRt(c(1000, 3000)) %>%
filterMz(c(120, 135))
x[precursorIntensity(x) > 11000000, ]
}Filtering on-disk is much faster thank to lazy evaluation. See Figure 1c in the pre-print.
x_filt <- filter_ms(x_dsk2)
filter_ms(x_mem)## MSn experiment data ("MSnExp")
## Object size in memory: 13.5 Mb
## - - - Spectra data - - -
## MS level(s): 2
## Number of spectra: 2927
## MSn retention times: 19:3 - 49:55 minutes
## - - - Processing information - - -
## Data loaded: Thu May 7 19:51:37 2020
## Data [logically] subsetted 4668 spectra: Thu May 7 19:52:25 2020
## Filter: select retention time [1000-3000] and MS level(s), 2 [Thu May 7 19:52:29 2020]
## Filter: trim MZ [120..135] on MS level(s) 2.
## Data [logically] subsetted 2927 spectra: Thu May 7 19:52:38 2020
## MSnbase version: 2.14.0
## - - - Meta data - - -
## phenoData
## rowNames:
## TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz
## varLabels: sampleNames
## varMetadata: labelDescription
## Loaded from:
## TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01-20141210.mzML.gz
## protocolData: none
## featureData
## featureNames: F1.S0256 F1.S0347 ... F1.S4746 (2927 total)
## fvarLabels: spectrum
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'x_filt[[1227]]## Object of class "Spectrum2"
## Precursor: 567.337
## Retention time: 31:6
## Charge: 2
## MSn level: 2
## Peaks count: 15
## Total ion count: 34649479writeMSData3 Prototyping: MSnbaseBoxCar
Reference: BoxCar acquisition method enables single-shot proteomics at a depth of 10,000 proteins in 100 minutes.
Package home page: http://lgatto.github.io/MSnbaseBoxCar/
library(MSnbaseBoxCar)
bcf <-
dir(system.file("extdata", package = "MSnbaseBoxCar"),
pattern = "boxcar.mzML",
full.names = TRUE)Read the data
bc <- readMSData(bcf, mode = "onDisk")
bc## MSn experiment data ("OnDiskMSnExp")
## Object size in memory: 0.04 Mb
## - - - Spectra data - - -
## MS level(s): 1
## Number of spectra: 16
## MSn retention times: 0:0 - 0:5 minutes
## - - - Processing information - - -
## Data loaded [Thu May 7 19:52:43 2020]
## MSnbase version: 2.14.0
## - - - Meta data - - -
## phenoData
## rowNames: boxcar.mzML
## varLabels: sampleNames
## varMetadata: labelDescription
## Loaded from:
## boxcar.mzML
## protocolData: none
## featureData
## featureNames: F1.S01 F1.S02 ... F1.S16 (16 total)
## fvarLabels: fileIdx spIdx ... spectrum (35 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'First full spectrum and 3 first BoxCar spectra
p <- plot(bc[1:4])
Identify sets of BoxCar spectra
fData(bc)$filterString## [1] "FTMS + p NSI Full ms [375.0000-1800.0000]"
## [2] "FTMS + p NSI SIM msx ms [299.0000-1701.0000, 299.0000-351.0000, 449.0000-501.0000, 599.0000-651.0000, 749.0000-801.0000, 899.0000-951.0000, 1049.0000-1101.0000, 1199.0000-1251.0000, 1349.0000-1401.0000, 1499.0000-1551.0000, 1649.0000-1701.0000]"
## [3] "FTMS + p NSI SIM msx ms [349.0000-1751.0000, 349.0000-401.0000, 499.0000-551.0000, 649.0000-701.0000, 799.0000-851.0000, 949.0000-1001.0000, 1099.0000-1151.0000, 1249.0000-1301.0000, 1399.0000-1451.0000, 1549.0000-1601.0000, 1699.0000-1751.0000]"
## [4] "FTMS + p NSI SIM msx ms [399.0000-1801.0000, 399.0000-451.0000, 549.0000-601.0000, 699.0000-751.0000, 849.0000-901.0000, 999.0000-1051.0000, 1149.0000-1201.0000, 1299.0000-1351.0000, 1449.0000-1501.0000, 1599.0000-1651.0000, 1749.0000-1801.0000]"
## [5] "FTMS + p NSI Full ms [375.0000-1800.0000]"
## [6] "FTMS + p NSI SIM msx ms [299.0000-1701.0000, 299.0000-351.0000, 449.0000-501.0000, 599.0000-651.0000, 749.0000-801.0000, 899.0000-951.0000, 1049.0000-1101.0000, 1199.0000-1251.0000, 1349.0000-1401.0000, 1499.0000-1551.0000, 1649.0000-1701.0000]"
## [7] "FTMS + p NSI SIM msx ms [349.0000-1751.0000, 349.0000-401.0000, 499.0000-551.0000, 649.0000-701.0000, 799.0000-851.0000, 949.0000-1001.0000, 1099.0000-1151.0000, 1249.0000-1301.0000, 1399.0000-1451.0000, 1549.0000-1601.0000, 1699.0000-1751.0000]"
## [8] "FTMS + p NSI SIM msx ms [399.0000-1801.0000, 399.0000-451.0000, 549.0000-601.0000, 699.0000-751.0000, 849.0000-901.0000, 999.0000-1051.0000, 1149.0000-1201.0000, 1299.0000-1351.0000, 1449.0000-1501.0000, 1599.0000-1651.0000, 1749.0000-1801.0000]"
## [9] "FTMS + p NSI Full ms [375.0000-1800.0000]"
## [10] "FTMS + p NSI SIM msx ms [299.0000-1701.0000, 299.0000-351.0000, 449.0000-501.0000, 599.0000-651.0000, 749.0000-801.0000, 899.0000-951.0000, 1049.0000-1101.0000, 1199.0000-1251.0000, 1349.0000-1401.0000, 1499.0000-1551.0000, 1649.0000-1701.0000]"
## [11] "FTMS + p NSI SIM msx ms [349.0000-1751.0000, 349.0000-401.0000, 499.0000-551.0000, 649.0000-701.0000, 799.0000-851.0000, 949.0000-1001.0000, 1099.0000-1151.0000, 1249.0000-1301.0000, 1399.0000-1451.0000, 1549.0000-1601.0000, 1699.0000-1751.0000]"
## [12] "FTMS + p NSI SIM msx ms [399.0000-1801.0000, 399.0000-451.0000, 549.0000-601.0000, 699.0000-751.0000, 849.0000-901.0000, 999.0000-1051.0000, 1149.0000-1201.0000, 1299.0000-1351.0000, 1449.0000-1501.0000, 1599.0000-1651.0000, 1749.0000-1801.0000]"
## [13] "FTMS + p NSI Full ms [375.0000-1800.0000]"
## [14] "FTMS + p NSI SIM msx ms [299.0000-1701.0000, 299.0000-351.0000, 449.0000-501.0000, 599.0000-651.0000, 749.0000-801.0000, 899.0000-951.0000, 1049.0000-1101.0000, 1199.0000-1251.0000, 1349.0000-1401.0000, 1499.0000-1551.0000, 1649.0000-1701.0000]"
## [15] "FTMS + p NSI SIM msx ms [349.0000-1751.0000, 349.0000-401.0000, 499.0000-551.0000, 649.0000-701.0000, 799.0000-851.0000, 949.0000-1001.0000, 1099.0000-1151.0000, 1249.0000-1301.0000, 1399.0000-1451.0000, 1549.0000-1601.0000, 1699.0000-1751.0000]"
## [16] "FTMS + p NSI SIM msx ms [399.0000-1801.0000, 399.0000-451.0000, 549.0000-601.0000, 699.0000-751.0000, 849.0000-901.0000, 999.0000-1051.0000, 1149.0000-1201.0000, 1299.0000-1351.0000, 1449.0000-1501.0000, 1599.0000-1651.0000, 1749.0000-1801.0000]"tmp1 <- bc_groups(bc)
fData(tmp1)$bc_groups## [1] NA 1 1 1 NA 2 2 2 NA 3 3 3 NA 4 4 4Remove non-BoxCar spectra
tmp2 <- filterBoxCar(tmp1)
fData(tmp2)$bc_groups## [1] 1 1 1 2 2 2 3 3 3 4 4 4tmp2## MSn experiment data ("OnDiskMSnExp")
## Object size in memory: 0.04 Mb
## - - - Spectra data - - -
## MS level(s): 1
## Number of spectra: 12
## MSn retention times: 0:0 - 0:5 minutes
## - - - Processing information - - -
## Data loaded [Thu May 7 19:52:43 2020]
## MSnbase version: 2.14.0
## - - - Meta data - - -
## phenoData
## rowNames: boxcar.mzML
## varLabels: sampleNames
## varMetadata: labelDescription
## Loaded from:
## boxcar.mzML
## protocolData: none
## featureData
## featureNames: F1.S02 F1.S03 ... F1.S16 (12 total)
## fvarLabels: fileIdx spIdx ... bc_groups (36 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'bc_plotly(tmp2[1:3])## Loading required namespace: plotlyRemove peaks outside of BoxCar segments
tmp3 <- bc_zero_out_box(tmp2)
bc_plotly(tmp3[1:3])Combine BoxCar spectra and segments into a new full scan
res <- combineSpectra(tmp3,
fcol = "bc_groups",
method = boxcarCombine)
res## MSn experiment data ("MSnExp")
## Object size in memory: 0.34 Mb
## - - - Spectra data - - -
## MS level(s): 1
## Number of spectra: 4
## MSn retention times: 0:0 - 0:4 minutes
## - - - Processing information - - -
## Data converted from Spectra: Thu May 7 19:52:45 2020
## BoxCar processed [Thu May 7 19:52:45 2020]
## Spectra combined based on feature variable 'bc_groups' [Thu May 7 19:52:45 2020]
## MSnbase version: 2.14.0
## - - - Meta data - - -
## phenoData
## rowNames: 1
## varLabels: sampleNames
## varMetadata: labelDescription
## Loaded from:
## 1
## protocolData: none
## featureData
## featureNames: F1.S02 F1.S06 F1.S10 F1.S14
## fvarLabels: fileIdx spIdx ... bc_groups (36 total)
## fvarMetadata: labelDescription
## experimentData: use 'experimentData(object)'writeMSData(res, file = "boxcar2.mzML")Putting it all together with %>%
bc2 <- bc %>%
bc_groups() %>%
filterBoxCar() %>%
bc_zero_out_box() %>%
combineSpectra(fcol = "bc_groups",
method = boxcarCombine)