Peakclustering into pseudospectra with the highly connected subgraphs approach

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Description

Cluster peaks from an xsAnnotate object into pseudospectra

Arguments

object

xsAnnotate object

ajc

Weighted symbolic edge list as four column matrix ("x","y","cor","ps"). Columns x,y are peak indices, cor the edge value and ps the pseudospectrum index, where both peaks occur.

psg_list

additional vector ps pseudospectra indices, which are used in the clustering. If set to NULL all pseudospectra will be processed.

Details

In some cases, is the peak grouping after retentiontime with groupFWHM not enough to separate co-elution compounds. Therefore groupCorr use additional correlation analysis to achieve a separation. calcPC is part of this approach, which takes the calculated weighted edge list and performs the graph clustering. It returns an xsAnnotate object with further separated pseudospectra.

Methods

object = "xsAnnotate"

calcPC.hcs(object, ajc=NULL, psg_list=NULL)

Author(s)

Carsten Kuhl, ckuhl@ipb-halle.de

See Also

calcPC groupCorr highlyConnSG xsAnnotate-class

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