Group features using OpenMS

Source: R/generics.R, R/feature_groups-openms.R

Group and align features with OpenMS tools

groupFeaturesOpenMS(feat, ...)

# S4 method for class 'features'
groupFeaturesOpenMS(
  feat,
  rtalign = TRUE,
  QT = FALSE,
  maxAlignRT = 30,
  maxAlignMZ = 0.005,
  maxGroupRT = 12,
  maxGroupMZ = 0.005,
  extraOptsRT = NULL,
  extraOptsGroup = NULL,
  verbose = TRUE
)

# S4 method for class 'featuresSet'
groupFeaturesOpenMS(feat, ..., verbose = TRUE)

Arguments

feat

The features object with the features to be grouped.

...

Further parameters passed to the selected grouping algorithm.

rtalign

Set to TRUE to enable retention time alignment.

QT

If enabled, use FeatureLinkerUnlabeledQT instead of FeatureLinkerUnlabeled for feature grouping.

maxAlignRT, maxAlignMZ

Used for retention alignment. Maximum retention time or m/z difference (seconds/Dalton) for feature pairing. Sets -algorithm:pairfinder:distance_RT:max_difference and -algorithm:pairfinder:distance_MZ:max_difference otpions, respectively.

maxGroupRT, maxGroupMZ

as maxAlignRT and maxAlignMZ, but for grouping of features. Sets -algorithm:distance_RT:max_difference and -algorithm:distance_MZ:max_difference options, respectively.

extraOptsRT, extraOptsGroup

Named list containing extra options that will be passed to MapAlignerPoseClustering or FeatureLinkerUnlabeledQT/FeatureLinkerUnlabeled, respectively. Any options specified here will override any of the above. Example: extraOptsGroup=list("-algorithm:distance_RT:max_difference"=12) (corresponds to setting maxGroupRT=12). Set to NULL to ignore.

verbose

if FALSE then no text output will be shown.

Value

An object of a class which is derived from featureGroups.

Details

This function uses OpenMS to group features. This function is called when calling groupFeatures with algorithm="openms".

Retention times may be aligned by the MapAlignerPoseClustering TOPP tool. Grouping is achieved by either the FeatureLinkerUnlabeled or FeatureLinkerUnlabeledQT TOPP tools.

References

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

See also

groupFeatures for more details and other algorithms.