R: Data Structure for a collection of all pairwise alignments of...

clusterAlignment {flagme}

R Documentation

Data Structure for a collection of all pairwise alignments of GCMS runs

Description

Store the raw data and optionally, information regarding signal peaks for a number of GCMS runs

Usage

clusterAlignment(pD, runs=1:length(pD@rawdata), timedf=NULL,
               usePeaks=TRUE, verbose=TRUE, ...)

Arguments

`pD`	a `peaksDataset` object.
`runs`	vector of integers giving the samples to calculate set of pairwise alignments over.
`timedf`	list (length = the number of pairwise alignments) of matrices giving the expected time differences expected at each pair of peaks used with `usePeaks`=`TRUE`, passed to `peaksAlignment`
`usePeaks`	logical, `TRUE` uses `peakdata` list, `FALSE` uses `rawdata` list for computing similarity.
`verbose`	logical, whether to print out info.
`...`	other arguments passed to `peaksAlignment`

Details

clusterAlignment computes the set of pairwise alignments.

Value

clusterAlignment object

Author(s)

Mark Robinson, Riccardo Romoli

References

Mark D Robinson (2008). Methods for the analysis of gas chromatography - mass spectrometry data PhD dissertation University of Melbourne.

Examples

require(gcspikelite)

# paths and files
gcmsPath <- paste(find.package("gcspikelite"), "data", sep="/")
cdfFiles <- dir(gcmsPath, "CDF", full=TRUE)
eluFiles <- dir(gcmsPath, "ELU", full=TRUE)

# read data, peak detection results
pd <- peaksDataset(cdfFiles[1:2], mz=seq(50,550), rtrange=c(7.5,8.5))
pd <- addAMDISPeaks(pd, eluFiles[1:2])

ca <- clusterAlignment(pd, gap=0.5, D=0.05, df=30, metric=1, type=1)

[Package flagme version 1.43.0 Index]