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Topics - Tony

2
XCMS / Vectorized Colors for plotting XChromatogram
Dear Develops,

would it be possible for the plotting functions such as:

## XChromatograms {xcms}
## S4 method for signature 'XChromatogram,ANY'
## plot(x, col = "#00000060", lty = 1, type = "l", xlab = "retention time", ylab = "intensity", main = NULL, peakType = c("polygon", "point", "rectangle", "none"), peakCol = "#00000060", peakBg = "#00000020", peakPch = 1, ...)

## plotChromPeakDensity,XCMSnExp-method {xcms}         
## S4 method for signature 'XChromatograms'
##plotChromPeakDensity(object, param, col = "#00000060", xlab = "retention time", main = NULL, peakType = c("polygon", "point", "rectangle", "none"), peakCol = "#00000060", peakBg = "#00000020", peakPch = 1, simulate = TRUE, ...)

to have the arguments:
peakCol = "#00000060", peakBg = "#00000020" (maybe also peakPch = 1) to be able to take vectorized colors like in the argument col?

This would enable mor freedom whilst plotting.

kind regards
Tony

[attachment deleted by admin]
3
XCMS / Centroiding of profile-mode DDA data, MS2-level
Hello developpers/maintainers,

I would like to hear your advice on how to treat DDA (Data Dependent Aquisition) experiments, which were quired in profile-mode.
It is clear from the very nice vignette (https://github.com/jorainer/metabolomics2018) on how to do this for MS1-level, but the question is on how to proceed the MS2-level. Should the MS2-level be centroided also and how can this be achieved including serialisation via MSnbase/xcms?

Thanks for your help
Kind regards
Tony



4
XCMS / Scan numbering for DDA/IDA-experiments
Dear Forum,

we are conducting metabolomic experiments using a AB Sciex 5600 TripleToF with DDA (Data Dependendent Aquisition) unsing R 3.6.0 under MSnbase (2.9.5) and xcms (3.5.5).
So we have MS1-scans and MS2-scans intrinsically in the raw data files.

The question here refers, on how to obtain the correct number of scans per peak in one file. The raw data was read with:
readMSData(files = files, pdata = new("NAnnotatedDataFrame", pd), msLevel. = 1)

Given the information from the function chromPeaks(object, bySample = FALSE, rt = numeric(), mz = numeric(), ppm = 0, type = "any"), this results in the following table.

               mz    mzmin    mzmax     rt  rtmin  rtmax      into      intb     maxo  sn egauss mu sigma  h  f dppm scale scpos scmin scmax lmin lmax sample is_filled
CP000001 185.0415 185.0409 185.0423 46.568 40.745 53.293 1623.3019 1605.9049 193.8009  25     NA NA    NA NA  6    1     9   169   160   178  148  185      1         0
CP000002 185.0419 185.0409 185.0429  3.887  0.724  6.577  763.4537  755.4926 170.2468  21     NA NA    NA NA  6    4     7    15     8    22    3   25      1         0
CP000003 512.8859 512.8845 512.8887 51.321 49.069 52.634  322.0898  319.1189 175.0130 174     NA NA    NA NA  7    8     7   182   175   189   87   93      1         0
CP000004 271.9464 271.9443 271.9484 51.321 48.780 53.293  303.1867  299.2378 142.4416 141     NA NA    NA NA  8    8     7   182   175   189   87   95      1         0
CP000005 385.9267 385.9250 385.9298 51.321 48.780 53.293  275.9011  271.9522 131.7186 131     NA NA    NA NA  9    5     7   182   175   189   87   95      1         0
CP000006 498.9059 498.9042 498.9077 50.666 49.069 53.293  256.1620  252.5414 133.5325 133     NA NA    NA NA 10    7     7   181   174   188   87   94      1         0

Is it okay to use the colums "scmin" "scmax", i.e. to compute scmax - scmin to get the correct number of scans for each peak,
or is there a need to take into account, that several scans need to be omitted for MS2-scans?

Basically the question (for DDA-experiments) simply condenses on how the scan numbering works:
How are the MS1-scans are numbered intrinsically?
How are the MS2-scans are numbered intrinsically?

By the way, what is the meaning of the columns lmin lmax? I could not find the meaning in the documentation of  chromPeaks() ...

Thanks for an answer.

kind regards
Tony
5
XCMS / findChromPeaks-centWave {xcms} - Prefilter Settings and Code Documentation
Dear Forum,

I would like to inquire about the prefilter setting for the function findChromPeaks-centWave {xcms}.

I am using R 3.5.3. under Windows7 (64bit) with packageVersion("MSnbase") ‘2.8.3’ and packageVersion("xcms") ‘3.4.4’.

Concerning the prefilter-parameter, here the code documentation says:

 CentWaveParam(ppm = 25, peakwidth = c(20, 50), 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())

prefilter
numeric(2): c(k, I) specifying the prefilter step for the first analysis step (ROI detection). Mass traces are only retained if they contain at least k peaks with intensity >= I.

For this documentation/explanation, is the term "peak" right here, or is rather "scans" the more adequate word.
From my understanding of the documentation of the prefilter, a peak (consisting of several(10-20) scan points) has to have more than k scans of intensity I.

Is that right?

thanks
Tony
6
XCMS / Question regarding the plot-methods {MSnbase}, type = "XIC"
Dear Maintainers,

after having get acquainted with xcms, i.e. rather MSnbase, here specifically with regard to the wonderful plotting functions (plot-methods {MSnbase}) available in MSnbase, a question came up, which I am not able to solve by myself...

More specifically, I am referring to this adopted demo code available from:

plot-methods {MSnbase} - R Documentation
Plotting 'MSnExp' and 'Spectrum' object(s)

I am using R.3.5.3 under Windows7 with packageVersion("MSnbase") ‘2.8.3’ and packageVersion("xcms") ‘3.4.4’.

Here is the demo code (last 2 lines adopted):

## Load profile-mode LC-MS files
library(msdata)
od <- readMSData(dir(system.file("sciex", package = "msdata"),
                     full.names = TRUE), mode = "onDisk")
## Restrict the MS data to signal for serine
serine <- filterMz(filterRt(od, rt = c(175, 190)), mz = c(106.04, 106.06))
plot(serine, type = "XIC")
abline(v = 181.0, col = "red", lty = 2)
abline(h = 106.05, col = "red", lty = 2)

The question is: why are the two lines (vertival and horizontal) only drawn for the last sample and not for all samples?
I think this is related to the underling layout function used in this plot, i.e. plot(..., type = "XIC"), but I am not able to solve the problem by myself...

thanks
Tony