uses the FeatureFinderMetabo TOPP tool (see http://www.openms.de) to find features.
findFeaturesOpenMS(
analysisInfo,
noiseThrInt = 1000,
chromSNR = 3,
chromFWHM = 5,
mzPPM = 10,
reEstimateMTSD = TRUE,
traceTermCriterion = "sample_rate",
traceTermOutliers = 5,
minSampleRate = 0.5,
minTraceLength = 3,
maxTraceLength = -1,
widthFiltering = "fixed",
minFWHM = 1,
maxFWHM = 30,
traceSNRFiltering = FALSE,
localRTRange = 10,
localMZRange = 6.5,
isotopeFilteringModel = "metabolites (5% RMS)",
MZScoring13C = FALSE,
useSmoothedInts = TRUE,
extraOpts = NULL,
intSearchRTWindow = 3,
useFFMIntensities = FALSE,
verbose = TRUE
)A data.frame with Analysis information.
Noise intensity threshold. Sets algorithm:common:noise_threshold_int option.
Minimum S/N of a mass trace. Sets algorithm:common:chrom_peak_snr option.
Expected chromatographic peak width (in seconds). Sets algorithm:common:chrom_fwhm option.
Allowed mass deviation (ppm) for trace detection. Sets algorithm:mtd:mass_error_ppm.
If TRUE then enables dynamic re-estimation of m/z variance during mass trace collection
stage. Sets algorithm:mtd:reestimate_mt_sd.
Termination criterion for the extension of mass traces. See
FeatureFinderMetabo.
Sets the algorithm:mtd:trace_termination_criterion, algorithm:mtd:trace_termination_outliers and
algorithm:mtd:min_sample_rate options, respectively.
Minimum/Maximum length of mass trace (seconds). Set negative value for maxlength
to disable maximum. Sets algorithm:mtd:min_trace_length and algorithm:mtd:min_trace_length,
respectively.
Enable filtering of unlikely peak widths. See
FeatureFinderMetabo.
Sets algorithm:epd:width_filtering, algorithm:epd:min_fwhm and algorithm:epd:max_fwhm,
respectively.
If TRUE then apply post-filtering by signal-to-noise ratio after smoothing. Sets the
algorithm:epd:masstrace_snr_filtering option.
Retention/MZ range where to look for coeluting/isotopic mass traces. Sets the
algorithm:ffm:local_rt_range and algorithm:ffm:local_mz_range options, respectively.
Remove/score candidate assemblies based on isotope intensities. See
FeatureFinderMetabo.
Sets the algorithm:ffm:isotope_filtering_model option.
Use the 13C isotope as the expected shift for isotope mass traces. See
FeatureFinderMetabo.
Sets algorithm:ffm:mz_scoring_13C.
If TRUE then use LOWESS intensities instead of raw intensities. Sets the
algorithm:ffm:use_smoothed_intensities option.
Named list containing extra options that will be passed to FeatureFinderMetabo. Any
options specified here will override any of the above. Example:
extraOpts=list("-algorithm:common:noise_threshold_int"=1000) (corresponds to setting
noiseThrInt=1000). Set to NULL to ignore.
Retention time window (in seconds, +/- feature retention time) that is used to find the closest data point to the retention time to obtain the intensity of a feature (this is needed since OpenMS does not provide this data).
If TRUE then peak intensities are directly loaded from FeatureFinderMetabo
output. Otherwise, intensities are loaded afterwards from the input mzML files, which is potentially much
slower, especially with many analyses files. However, useFFMIntensities=TRUE is still somewhat experimental,
may be less accurate and requires a recent version of OpenMS (>=2.7).
If set to FALSE then no text output is shown.
An object of a class which is derived from features.
This function uses OpenMS to automatically find features. This function is called when calling findFeatures with
algorithm="openms".
This functionality has been tested with OpenMS version >= 2.0. Please make sure it is installed and
configured, e.g. by installing patRoonExt or configuring the path of the binaries with
the patRoon.path.OpenMS option or the system PATH variable.
The file format of analyses must be mzML.
The input MS data files need to be centroided. The convertMSFiles function can be used to
centroid data.
findFeaturesOpenMS uses multiprocessing to parallelize
computations. Please see the parallelization section in the handbook for
more details and patRoon options for configuration
options.
Note that for caching purposes, the analyses files must always exist on the local host computer, even if it is not participating in computations.
Rost HL, Sachsenberg T, Aiche S, Bielow C, Weisser H, Aicheler F, Andreotti S, Ehrlich H, Gutenbrunner P, Kenar E, Liang X, Nahnsen S, Nilse L, Pfeuffer J, Rosenberger G, Rurik M, Schmitt U, Veit J, Walzer M, Wojnar D, Wolski WE, Schilling O, Choudhary JS, Malmstrom L, Aebersold R, Reinert K, Kohlbacher O (2016).
“OpenMS: a flexible open-source software platform for mass spectrometry data analysis.”
Nature Methods, 13(9), 741–748.
doi:10.1038/nmeth.3959
.
pugixml (via Rcpp) is used to process OpenMS XML output.
Eddelbuettel D (2013).
Seamless R and C++ Integration with Rcpp.
Springer, New York.
doi:10.1007/978-1-4614-6868-4
, ISBN 978-1-4614-6867-7.
Eddelbuettel D, Balamuta J (2018).
“Extending R with C++: A Brief Introduction to Rcpp.”
The American Statistician, 72(1), 28-36.
doi:10.1080/00031305.2017.1375990
.
Eddelbuettel D, François R (2011).
“Rcpp: Seamless R and C++ Integration.”
Journal of Statistical Software, 40(8), 1–18.
doi:10.18637/jss.v040.i08
.
Eddelbuettel D, Francois R, Allaire J, Ushey K, Kou Q, Russell N, Ucar I, Bates D, Chambers J (2025).
Rcpp: Seamless R and C++ Integration.
R package version 1.1.0, https://www.rcpp.org.
1
findFeatures for more details and other algorithms.