alsace (version 1.8.0)

getPeakTable: Convert MCR results into an ordered peak table

Description

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.

Usage

getPeakTable(peakList, response = c("area", "height"), use.cor = TRUE, maxdiff = 0.2, plotIt = FALSE, ask = plotIt)

Arguments

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?

Value

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.

Details

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.

Examples

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")