getPeakTable: Convert MCR results into an ordered peak table
In rwehrens/alsace: ALS for the Automatic Chemical Exploration of mixtures

Description Usage Arguments Details Value Author(s) Examples

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.

1 2	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")