Automatically find features.
findFeatures(analysisInfo, algorithm, ..., verbose = TRUE)A data.frame with Analysis information.
A character string describing the algorithm that should be
used: "bruker", "openms", "xcms", "xcms3", "envipick", "sirius", "kpic2", "safd"
Further parameters passed to the selected feature finding algorithms.
If set to FALSE then no text output is shown.
An object of a class which is derived from features.
Several functions exist to collect features (i.e. retention and MS information that represent potential
compounds) from a set of analyses. All 'feature finders' return an object derived from the features
base class. The next step in a general workflow is to group and align these features across analyses with
groupFeatures. Note that some feature finders have a plethora of options which sometimes may have a
large effect on the quality of results. Fine-tuning parameters is therefore important, and the optimum is largely
dependent upon applied analysis methodology and instrumentation.
findFeatures is a generic function that will find features by one of the supported algorithms. The actual
functionality is provided by algorithm specific functions such as findFeaturesOpenMS and findFeaturesXCMS. While these
functions may be called directly, findFeatures provides a generic interface and is therefore usually preferred.
In most cases it will be necessary to centroid your MS input files. The only exception is Bruker,
however, you will still need centroided mzXML/mzML files for e.g. plotting chromatograms. In
this case the centroided MS files should be stored in the same directory as the raw Bruker .d
files. The convertMSFiles function can be used to centroid data.
The features output class and its methods and the algorithm specific functions:
findFeaturesBruker, findFeaturesOpenMS, findFeaturesXCMS, findFeaturesXCMS3, findFeaturesEnviPick, findFeaturesSIRIUS, findFeaturesKPIC2, findFeaturesSAFD