\HeaderA{group.mzClust}{Group Peaks via High Resolution Alignment}{group.mzClust}
\aliasA{group.mzClust,xcmsSet-method}{group.mzClust}{group.mzClust,xcmsSet.Rdash.method}
\keyword{methods}{group.mzClust}
\keyword{file}{group.mzClust}
\begin{Description}\relax
Runs high resolution alignment on the peaks stored in a
given xcmsSet.
\end{Description}
\begin{Usage}
\begin{verbatim}
groupedobject <- group(object, method="mzClust", mzppm = 20, mzabs = 0, minsamp = 1, minsampclass=0, minfrac=0)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{object}] a xcmsSet with peaks 
\item[\code{mzppm}] the relative error used for clustering/grouping in ppm (parts per million)
\item[\code{mzabs}] the absolute error used for clustering/grouping
\item[\code{minsamp}] set the minimum number of samples in one bin
\item[\code{minfrac}] set the minimum fraction of each class in one bin
\end{ldescription}
\end{Arguments}
\begin{Value}
Returns a xcmsSet with slots groups and groupindex set.
\end{Value}
\begin{References}\relax
Saira A. Kazmi, Samiran Ghosh, Dong-Guk Shin,
Dennis W. Hill and David F. Grant\\
\emph{Alignment of high resolution mass spectra: development of a heuristic
approach for metabolomics}.\\
Metabolomics, Vol. 2, No. 2, 75-83 (2006)
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{xcmsSet-class}{xcmsSet.Rdash.class}},
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## load xcms and faahKO Dataset
library(xcms)
library(faahKO)
data(faahko)
## group faahko data
##faahko_grouped <- group(faahko, method="mzClust")
## get groups
##groups <- groups(faahko_grouped)
## get grouped peak indices
##idx <- groupidx(faahko_grouped)
\end{ExampleCode}
\end{Examples}

