Description Usage Arguments Value Slots Note References See Also Examples
This method performs high resolution correspondence for single spectra samples.
The MzClustParam
class allows to specify all settings for the peak
grouping based on the mzClust algorithm.
Instances should be created with the MzClustParam
constructor.
sampleGroups
,sampleGroups<-
: getter and setter
for the sampleGroups
slot of the object.
ppm
,ppm<-
: getter and setter for the ppm
slot of the object.
absMz
,absMz<-
: getter and setter for the
absMz
slot of the object.
minFraction
,minFraction<-
: getter and setter for
the minFraction
slot of the object.
minSamples
,minSamples<-
: getter and setter for the
minSamples
slot of the object.
groupChromPeaks,XCMSnExp,MzClustParam
: performs high resolution peak
grouping for single spectrum metabolomics data.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | MzClustParam(
sampleGroups = numeric(),
ppm = 20,
absMz = 0,
minFraction = 0.5,
minSamples = 1
)
## S4 method for signature 'MzClustParam'
show(object)
## S4 method for signature 'MzClustParam'
sampleGroups(object)
## S4 replacement method for signature 'MzClustParam'
sampleGroups(object) <- value
## S4 method for signature 'MzClustParam'
ppm(object)
## S4 replacement method for signature 'MzClustParam'
ppm(object) <- value
## S4 method for signature 'MzClustParam'
absMz(object)
## S4 replacement method for signature 'MzClustParam'
absMz(object) <- value
## S4 method for signature 'MzClustParam'
minFraction(object)
## S4 replacement method for signature 'MzClustParam'
minFraction(object) <- value
## S4 method for signature 'MzClustParam'
minSamples(object)
## S4 replacement method for signature 'MzClustParam'
minSamples(object) <- value
## S4 method for signature 'XCMSnExp,MzClustParam'
groupChromPeaks(object, param, msLevel = 1L)
|
sampleGroups |
A vector of the same length than samples defining the
sample group assignments (i.e. which samples belong to which sample
group). This parameter is mandatory for the |
ppm |
|
absMz |
|
minFraction |
|
minSamples |
|
object |
For For all other methods: a `MzClustParam` object. |
value |
The value for the slot. |
param |
A |
msLevel |
|
The MzClustParam
function returns a MzClustParam
class instance with
all of the settings specified for high resolution single spectra peak
alignment.
For groupChromPeaks
: a XCMSnExp object with the results of the peak
grouping step (i.e. the features). These can be accessed with the
featureDefinitions()
method.
.__classVersion__,sampleGroups,ppm,absMz,minFraction,minSamples
See corresponding parameter above. .__classVersion__
stores
the version from the class. Slots values should exclusively be accessed
via the corresponding getter and setter methods listed above.
These methods and classes are part of the updated and modernized
xcms
user interface which will eventually replace the
group()
methods. All of the settings to the algorithm
can be passed with a MzClustParam object.
Calling groupChromPeaks
on an XCMSnExp
object will cause
all eventually present previous correspondence results to be dropped.
Saira A. Kazmi, Samiran Ghosh, Dong-Guk Shin, Dennis W. Hill
and David F. Grant
Alignment of high resolution mass spectra:
development of a heuristic approach for metabolomics.
Metabolomics,
Vol. 2, No. 2, 75-83 (2006)
The do_groupPeaks_mzClust()
core API function and group.mzClust()
for
the old user interface.
featureDefinitions()
and featureValues()
for methods to access peak
grouping results (i.e. the features).
XCMSnExp for the object containing the results of the peak grouping.
Other peak grouping methods:
groupChromPeaks-density
,
groupChromPeaks-nearest
,
groupChromPeaks()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Loading a small subset of direct injection, single spectrum files
library(msdata)
fticrf <- list.files(system.file("fticr", package = "msdata"),
recursive = TRUE, full.names = TRUE)
fticr <- readMSData(fticrf[1:2], msLevel. = 1, mode = "onDisk")
## Disable parallel processing for this example
register(SerialParam())
## Perform the MSW peak detection on these:
p <- MSWParam(scales = c(1, 7), peakThr = 80000, ampTh = 0.005,
SNR.method = "data.mean", winSize.noise = 500)
fticr <- findChromPeaks(fticr, param = p)
head(chromPeaks(fticr))
## Now create the MzClustParam parameter object: we're assuming here that
## both samples are from the same sample group.
p <- MzClustParam(sampleGroups = c(1, 1))
fticr <- groupChromPeaks(fticr, param = p)
## Get the definition of the features.
featureDefinitions(fticr)
|
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