metaMSsettings-class {metaMS} | R Documentation

## Class `"metaMSsettings"`

### Description

This class contains all settings needed to run the metaMS pipelines for LC-MS (`runLC`) and GC-MS (`runGC`). Slots `PeakPicking`, `Alignment` and `CAMERA` are simply handed over to the appropriate xcms and CAMERA functions; all other slots contain settings for metaMS functions.

### Objects from the Class

Objects can be created by calls of the form `metaMSsettings(...)`. See the example below.

### Slots

Note: all slots describing retention times or retention time differences use minutes and not seconds. If a slot is only relevant for either GCMS or LCMS, this is indicated explicitly.

`protocolName`:

  Object of class `"character"`: the name of the instrumental protocol, a unique identifier.

`chrom`:

  Object of class `"character"`: chromatography. Either "LC" or "GC".

`PeakPicking`:

  Object of class `"list"`: The parameters used for xcms peakpicking. See the arguments of `findPeaks`.

`Alignment`:

  Object of class `"list"`: The parameters used for grouping and alignment. `min.class.fraction` and `min.class.size` are used to calculate the `minsample` xcms parameter. `bws` is a vector of the two bandwidths used for grouping before and after retention time alignent. `missingratio` and `extraratio` are used to set the values for `missing` and `extra` as a function of the number of samples. LC only.

`CAMERA`:

  Object of class `"list"`: The parameters for CAMERA.

`match2DB.rtdiff`:

  Object of class `"numeric"`: the maximal difference in retention time to match each feature with the entry in the DB.

`match2DB.minfeat`:

  Object of class `"numeric"`: for LC, the minimal number of matching features within a retention time interval of width `rtval` before we speak of a hit. For GC, the minimal number of common masses for calculating a match factor.

`match2DB.rtval`:

  Object of class `"numeric"`: the tolerance in retention time for features used in annotation. LC only.

`match2DB.mzdiff`:

  Object of class `"numeric"`: the mass accuracy which is used if no error surface is provided. LC only.

`match2DB.ppm`:

  Object of class `"numeric"`: the minimum mass tolerance allowed when the error surface is used. LC only.

`match2DB.simthresh`:

  Object of class `"numeric"`: the minimal match factor to speak of a hit. GC only.

`match2DB.timeComparison`:

  Object of class `"character"`: either "rt" or "RI". GC only.

`match2DB.RIdiff`:

  Object of class `"numeric"`: maximal retention index difference with DB entry (GC only).

`DBconstruction.minfeat`:

  Object of class `"numeric"`: the minimum number of features necessary to include a compound in the DB.

`DBconstruction.rttol`:

  Object of class `"numeric"`: the tolerance in retention time to match experimental features with the reference table.

`DBconstruction.mztol`:

  Object of class `"numeric"`: the tolerance in m/z (in dalton) to match experimental features with the reference table. LC only.

`DBconstruction.minintens`:

  Object of class `"numeric"`: the minimum intensity for a feature to be included in the list. GC only.

`DBconstruction.intensityMeasure`:

  Object of class `"character"`: either `"into"` or `"maxo"`. GC only.

`DBconstruction.DBthreshold`:

  Object of class `"numeric"`: minimal match factor with an external DB for a pseudospectrum to be included in the DB of standards. GC only.

`matchIrrelevants.irrelevantClasses`:

  Object of class `"character"`: classes of compounds are considered as irrelevant (a vector of string constants, which should exactly match the `Class` element in the DB entries). GC only.

`matchIrrelevants.simthresh`:

  Object of class `"numeric"`: the minimal match factor to speak of a hit. GC only.

`matchIrrelevants.timeComparison`:

  Object of class `"character"`: either "rt" or "RI". GC only.

`matchIrrelevants.rtdiff`:

  Object of class `"numeric"`: maximal retention time difference between two unknowns - this can be set to a very high value if a pattern is to be removed whatever the retention time. GC only.

`matchIrrelevants.RIdiff`:

  Object of class `"numeric"`: maximal retention index difference between two unknowns - this can be set to a very high value if a pattern is to be removed whatever the Retention Index. GC only.

`betweenSamples.min.class.fraction`:

  Object of class `"numeric"`: fraction of samples in which a pseudospectrum is present before it is regarded as an unknown. GC only.

`betweenSamples.min.class.size`:

  Object of class `"numeric"`: absolute number of samples in which a pseudospectrum is present before it is regarded as an unknown. GC only.

`betweenSamples.timeComparison`:

  Object of class `"character"`: either "rt" or "RI". GC only.

`betweenSamples.rtdiff`:

  Object of class `"numeric"`: max retention time difference between pseudospectra in different samples. GC only.

`betweenSamples.RIdiff`:

  Object of class `"numeric"`: max retention index difference between pseudospectra in different samples. GC only.

`betweenSamples.simthresh`:

  Object of class `"numeric"`: similarity threshold fo comparing pseudospectra in different samples. GC only.

### Methods

metaSetting<-

  `signature(object = "metaMSsettings")`: change values in a metaMSsettings object.

metaSetting

  `signature(object = "metaMSsettings")`: get values from a metaMSsettings object.

show

  `signature(object = "metaMSsettings")`: show a metaMSsettings object.

### Author(s)

Ron Wehrens

### See Also

`FEMsettings`

### Examples

    showClass("metaMSsettings")

    ## Not run:
    ## The three sets of settings are created as follows:
    Synapt.NP <- metaMSsettings(protocolName = "Synapt.QTOF.NP",
                                chrom = "LC",
                                PeakPicking = list(
                                  method = "matchedFilter",
                                  step = 0.05,
                                  fwhm = 20,
                                  snthresh = 4,
                                  max = 50),
                                Alignment = list(
                                  min.class.fraction = .3,
                                  min.class.size = 3,
                                  mzwid = 0.1,
                                  bws = c(130, 10),
                                  missingratio = 0.2,
                                  extraratio = 0.1,
                                  retcormethod = "linear",
                                  retcorfamily = "symmetric",
                                  fillPeaks = TRUE),
                                CAMERA = list(
                                  perfwhm = 0.6,
                                  cor_eic_th = 0.7,
                                  ppm= 5))
    metaSetting(Synapt.NP, "match2DB") <- list(
                rtdiff = 1.5,
                rtval = .1,
                mzdiff = 0.005,
                ppm = 5,
                minfeat = 2)
    metaSetting(Synapt.NP, "DBconstruction") <- list(
                minfeat = 3,
                rttol = .3,
                mztol = .01)

    ## End(Not run)

[Package metaMS version 1.20.0 Index]