groupChromPeaks-mzClust {xcms} | R Documentation |
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.
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)
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 |
value |
The value for the slot. |
param |
A |
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,XCMSnExp-method
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
## 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") ## 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)