Data independent acquisition/SWATH support

[jorainer]

Enable analysis of data independent acquisition (including SWATH) data.

• peak detection in pockets/isolation windows.
• data structures for identified chromatographic peaks (issue Data structures for SWATH data #346).
• functionality to build MS2 spectra.
• vignette describing the new functionality.

concepts base on https://github.com/michaelwitting/metabolomics2018 from @michaelwitting

[jorainer]

Data structures for identified chrom peaks:

• it is possible to add arbitrary annotations to each chromatographic peak using the chromPeakData DataFrame. Default columns in that DataFrame are ms_level and is_filled, to enable SWATH support we will have there also a column isolationWindow that identifies in which isolation window the peak was identified.

[jorainer]

Peak detection within isolation windows is possible with the findChromPeaksIsolationWindow function. The isolation window (i.e. definition which spectra belong to which isolation window) can be specified with the isolationWindow parameter.

[jorainer]

For each MS1 peak we have then to

• identify fragment candidates (MS2 peaks) within the same rt window.
• extract chromatogram for all
• align chromatograms
• correlate chromatograms
• reconstruct MS2 spectrum from MS2 peaks with correlation > x

@michaelwitting, is that correct?

[sneumann]

Parts of that was done in a prototype using CAMERA, i.e. groupCorr() in a MS2 pocket gives a spectrum,
and then we "only" need to find from which MS1 precursor that might originate. My prototype
did not correlate the MS1 and MS2 chromatogram.
Would it be interesting to calculate and attach a "TIC" chromatogram for all MS2 peaks in a collected MS2 spectrum, since it will be smoother than the individual ones ? Yours, Steffen

[michaelwitting]

@jorainer, yes correct so far. I started from the MS1 peak. Checked in which pocket it might fall and got all the MS2 peaks that where within a certain RT range around the MS1 peak, e.g. +/- 0.1 minutes around RT of MS1 peak.
I have some prototype code here for the alignment and correlation. I will finish it and push it this evening.

[sneumann]

Side-note: there is public SWATH data as mzML in
https://www.ebi.ac.uk/metabolights/MTBLS297
I could create a package mtbls297 similar to mtbls2,
which could be used in a new vignette ? The vignette could live
in mtbls297, saving us the hassle to have another few dozens of
raw data in suggests for xcms. Yours, Steffen

[michaelwitting]

Sounds like a good idea. Since you know the people from this dataset quite well, there should be also no political problems ;-)

[jorainer]

Yes @sneumann ! That would be awesome! So far I am @michaelwitting 's toy data set and I was trying to talk him into adding that to the msdata package.

[jorainer]

Actually, it might still be helpfull to add one SWATH mzML file to msdata to have something for the unit tests...

[michaelwitting]

No problem. Just take my toy data set. We can have for the next bioconductor release.

[sneumann]

Get files from mtbls297 package:

library(Risa)
library(xcms)

ISAmtbls297 <- readISAtab(find.package("mtbls297"))
assay <- ISAmtbls297@assay.tabs[[1]]
msfiles <- paste(find.package("mtbls297"), "mzML",
                 assay@assay.file$"Derived Spectral Data File",
                 sep="/")

Works for above AB Sciex, adn Bruker mid-band CID so far.
MS1 peak picking:

cwp <- CentWaveParam(ppm = 25, peakwidth = c(10, 20), snthresh = 10,
  prefilter = c(3, 100), mzCenterFun = "wMean", integrate = 1L,
  mzdiff = -0.001, fitgauss = FALSE, noise = 0, verboseColumns = FALSE,
  roiList = list(), firstBaselineCheck = TRUE, roiScales = numeric())

raw_data <- readMSData(msfiles, mode = "onDisk")

## Perform the peak detection using the settings defined above.
mtbls297 <- findChromPeaks(raw_data, param = cwp, BPPARAM = MulticoreParam())

Now get the SWATH data:

x2 <- findChromPeaksIsolationWindow(mtbls297, 
                                    param = cwp, 
                                    BPPARAM = MulticoreParam())
cpd <- chromPeakData(x2)

Although no data yet:

> head(cpd)
DataFrame with 6 rows and 6 columns
        ms_level is_filled isolationWindow isolationWindowTargetMZ
       <integer> <logical>        <factor>               <numeric>
CP0001         1     FALSE              NA                      NA
CP0002         1     FALSE              NA                      NA
CP0003         1     FALSE              NA                      NA
CP0004         1     FALSE              NA                      NA
CP0005         1     FALSE              NA                      NA
CP0006         1     FALSE              NA                      NA

[jorainer]

@sneumann, can you share the mtbls297 package somehow?

[jorainer]

The code to align Chromatogram objects and to correlate them will be implemented in methods #379 and #380 - these might eventually then go to MSnbase.