Uses the 'Find Molecular Features' (FMF) algorithm of Bruker DataAnalysis vendor software to find features.
findFeaturesBruker(
analysisInfo,
doFMF = "auto",
startRange = 0,
endRange = 0,
save = TRUE,
close = save,
verbose = TRUE
)
A data.frame
with Analysis information.
Run the 'Find Molecular Features' algorithm before loading compounds. Valid options are: "auto"
(run FMF automatically if current results indicate it is necessary) and "force"
(run FMF always, even
if cached results exist). Note that checks done if doFMF="auto"
are fairly simplistic, hence set
doFMF="force"
if feature data needs to be updated.
Start/End retention range (seconds) from which to collect features. A 0 (zero) for
endRange
marks the end of the analysis.
If TRUE
then Bruker files are closed and saved after
processing with DataAnalysis, respectively. Setting close=TRUE
prevents that many analyses might be opened simultaneously in DataAnalysis,
which otherwise may use excessive memory or become slow. By default
save
is TRUE
when close
is TRUE
, which is
likely what you want as otherwise any processed data is lost.
If set to FALSE
then no text output is shown.
An object of a class which is derived from features
.
This function uses Bruker to automatically find features. This function is called when calling findFeatures
with
algorithm="bruker"
.
The resulting 'compounds' are transferred from DataAnalysis and stored as features.
This algorithm only works with Bruker data files (.d
extension) and requires Bruker DataAnalysis
and the RDCOMClient package to be installed. Furthermore, DataAnalysis combines multiple related masses in a
feature (e.g. isotopes, adducts) but does not report the actual (monoisotopic) mass of the feature.
Therefore, it is simply assumed that the feature mass equals that of the highest intensity mass peak.
If any errors related to DCOM
appear it might be necessary to
terminate DataAnalysis (note that DataAnalysis might still be running as a
background process). The ProcessCleaner
application installed
with DataAnalayis can be used for this.
findFeatures
for more details and other algorithms.