PeakGrouper: Peak grouping with hierarchical clustering

In speaq: Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations

Peak grouping with hierarchical clustering

Description

This functions groups the peaks obtained after wavelet based peak detection (with the 'getWaveletPeaks' function).

Usage

PeakGrouper(
  Y.peaks,
  grouping.window.width = 100,
  verbose = FALSE,
  min.samp.grp = 1,
  max.dupli.prop = 0.25,
  maxClust = 10,
  Jaccard.regroup.threshold = 0.25,
  linkage = "average"
)

Arguments

Y.peaks	data frame obtained from the 'getWaveletPeaks' function.
grouping.window.width	The width of the sliding window (in measurement points). Measurements are taken for when this sliding window is taken too small, but best set this too a value that a normal peak is comfortably in a window. Note if large shifts occur in your dataset (like in the wine dataset) it is best to set this parameter larger.
verbose	If set to TRUE the window selection process is documented in real time (default = FALSE).
min.samp.grp	The minimal amount of samples needed to form a group, see hclust.grouping.
max.dupli.prop	The maximal duplication proportion allowed for a group to be considered a single group, see hclust.grouping.
maxClust	The maximum number of clusters (depth of the tree), see hclust.grouping.
Jaccard.regroup.threshold	If 2 neighbouring groups have a jaccard index smaller than this 'Jaccard.regroup.threshold' (indicating that they are quite complementary as they have little peaks samples in common), then they are merged and regrouped. This situation can occur if a group is accidentally cut in half by the window approach.
linkage	The linkage to be used in the hierarchical clustering. See the 'method' argument in hclust.

Value

Returns a data frame with grouped peaks. Peaks in a group are indicated with an identical peakIndex

Author(s)

Charlie Beirnaert, [e-mail]

See Also

hclust.grouping

Examples

subset <- GetWinedata.subset()
# to reduce the example time we only select spectra 1 & 2
subset.spectra = as.matrix(subset$Spectra)[1:2,] 
subset.ppm = as.numeric(subset$PPM)

test.peaks <- getWaveletPeaks(Y.spec=subset.spectra, 
                              X.ppm=subset.ppm ,
                              nCPU = 1) # nCPU set to 2 for the vignette build

test.grouped <- PeakGrouper(Y.peaks = test.peaks)

speaq documentation built on May 23, 2022, 5:06 p.m.