MassSpecSettings_GroupFeatures_xcms3_peakdensity
Source:R/class_S3_MassSpecSettings.R
MassSpecSettings_GroupFeatures_xcms3_peakdensity.Rd
Settings for grouping features (i.e., chromatographic peaks) across mzML/mzXML files using the package xcms (version 3) with the algorithm peakDensity. The function uses the package patRoon in the background.
Usage
MassSpecSettings_GroupFeatures_xcms3_peakdensity(
bw = 5,
minFraction = 1,
minSamples = 1,
binSize = 0.008,
maxFeatures = 100
)
Arguments
- bw
numeric(1) defining the bandwidth (standard deviation of the smoothing kernel) to be used. This argument is passed to the
density()
method.- minFraction
numeric(1) defining the minimum fraction of analyses in at least one analysis replicate group in which the features have to be present to be considered as a feature group.
- minSamples
numeric(1) with the minimum number of analyses in at least one analysis replicate group in which the features have to be detected to be considered a feature group.
- binSize
numeric(1) defining the size of the overlapping slices in mz dimension.
- maxFeatures
numeric(1) with the maximum number of feature groups to be identified in a single mz slice.
Value
A ProcessingSettings S3 class object with subclass MassSpecSettings_GroupFeatures_xcms3_peakdensity.
Details
See the groupFeaturesXCMS3 function from the patRoon package for more information and requirements.
References
Helmus R, ter Laak TL, van Wezel AP, de Voogt P, Schymanski EL (2021). “patRoon: open source software platform for environmental mass spectrometry based non-target screening.” Journal of Cheminformatics, 13(1). doi:10.1186/s13321-020-00477-w .
Helmus R, van de Velde B, Brunner AM, ter Laak TL, van Wezel AP, Schymanski EL (2022). “patRoon 2.0: Improved non-target analysis workflows including automated transformation product screening.” Journal of Open Source Software, 7(71), 4029. doi:10.21105/joss.04029 .
Smith, C.A., Want, E.J., O'Maille, G., Abagyan,R., Siuzdak, G. (2006). “XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching and identification.” Analytical Chemistry, 78, 779--787.
Tautenhahn R, Boettcher C, Neumann S (2008). “Highly sensitive feature detection for high resolution LC/MS.” BMC Bioinformatics, 9, 504.
Benton HP, Want EJ, Ebbels TMD (2010). “Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data.” BIOINFORMATICS, 26, 2488.