getPeakTable {alsace} | R Documentation |
Function returns a matrix of intensities, where rows correspond to (aligned) features and columns to objects (samples, injections, ...). The function performs a complete linkage clustering of retention times across all samples, and cuts at a height given by the user (which can be interpreted as the maximal inter-cluster retention time difference). If two peaks from the same sample are assigned to the same cluster, and error message is given.
getPeakTable(peakList, response = c("area", "height"), use.cor = TRUE, maxdiff = 0.2, plotIt = FALSE, ask = plotIt)
peakList |
A nested list of peak tables: the first level is the sample, and the second level is the component. Every component is described by a matrix where every row is one peak, and the columns contain information on retention time, full width at half maximum (FWHM), peak width, height, and area. |
response |
An indicator whether peak area or peak height is to be used as intensity measure. Default is peak area. |
use.cor |
Logical, indicating whether to use corrected retention times (by default) or raw retention times (not advised!). |
maxdiff |
Height at which the complete linkage dendrogram will be cut. Can be interpreted as the maximal inter-cluster retention time difference. |
plotIt |
Logical. If TRUE, for every component a stripplot will be shown indicating the clustering. |
ask |
Logical. Ask before showing new plot? |
If one sees warnings about peaks from the same sample sharing a
cluster label, one option is to reduce the maxdiff
variable -
this, however, will increase the number of clusters. Another option is
to filter the peaks on intensity: perhaps one of the two peaks in the
cluster is only a very small feature.
The function returns a data frame where the first couple of columns contain meta-information on the features (component, peak, retention time) and the other columns contain the intensities of the features in the individual injections.
Ron Wehrens
data(teaMerged) pks <- getAllPeaks(teaMerged$CList, span = 11) warping.models <- correctRT(teaMerged$CList, reference = 2, what = "models") pks.corrected <- correctPeaks(pks, warping.models) pkTab <- getPeakTable(pks.corrected, response = "area")