Feature compounding aims at identifying and grouping LC-MS features
representing different ions or adducts (including isotopes) of the same
originating compound.
The MsFeatures package
provides a general framework and functionality to group features based on
different properties. The groupFeatures
methods for XcmsExperiment()
or
XCMSnExp objects implemented in xcms
extend these to enable
the compounding of LC-MS data considering also e.g. feature peak shaped.
Note that these functions simply define feature groups but don't
actually aggregate or combine the features.
See MsFeatures::groupFeatures()
for an overview on the general feature
grouping concept as well as details on the individual settings and
parameters.
The available options for groupFeatures
on xcms
preprocessing results
(i.e. on XcmsExperiment
or XCMSnExp
objects after correspondence
analysis with groupChromPeaks()
) are:
Grouping by similar retention times:
groupFeatures-similar-rtime()
.Grouping by similar feature values across samples:
AbundanceSimilarityParam()
.Grouping by similar peak shape of extracted ion chromatograms:
EicSimilarityParam()
.
An ideal workflow grouping features should sequentially perform the above methods (in the listed order).
Compounded feature groups can be accessed with the featureGroups
function.
Usage
# S4 method for class 'XcmsResult'
featureGroups(object)
# S4 method for class 'XcmsResult'
featureGroups(object) <- value
Arguments
- object
an
XcmsExperiment()
orXCMSnExp()
object with LC-MS pre-processing results.- value
for
featureGroups<-
: replacement for the feature groups inobject
. Has to be of length 1 or length equal to the number of features inobject
.
See also
plotFeatureGroups()
for visualization of grouped features.