\HeaderA{KCsmart-package}{KCsmart}{KCsmart.Rdash.package}
\aliasA{KCsmart}{KCsmart-package}{KCsmart}
\keyword{package}{KCsmart-package}
\begin{Description}\relax
Multiple sample aCGH analysis using kernel convolution
\end{Description}
\begin{Details}\relax
\Tabular{ll}{
Package: & KCsmart\\
Type: & Package\\
Version: & 1.0\\
Date: & 2008-08-14\\
License: & GPL\\
}
Use the wrapper function 'calcSpm' to calculate the sample point matrix. Use 'findSigLevelTrad' to find a significance threshold using permutation based testing.
Use 'plot' to plot the sample point matrix or 'plotScaleSpace' to plot the significant regions over multiple scales (sigmas).
Use 'getSigSegments' to retrieve the significantly gained and lost regions using specific cutoffs.
\end{Details}
\begin{Author}\relax
Jorma de Ronde, Christiaan Klijn

Maintainer: Jorma de Ronde <j.d.ronde@nki.nl>
\end{Author}
\begin{References}\relax
Identification of cancer genes using a statistical framework for multiexperiment analysis of nondiscretized array CGH data.
Nucleic Acids Res. 2008 Feb;36(2):e13.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{calcSpm}{calcSpm}},  \code{\LinkA{findSigLevelTrad}{findSigLevelTrad}}, \code{\LinkA{findSigLevelFdr}{findSigLevelFdr}}, \code{\LinkA{plot}{plot}}, \code{\LinkA{plotScaleSpace}{plotScaleSpace}}, \code{\LinkA{getSigSegments}{getSigSegments}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(hsSampleData)
data(hsMirrorLocs)

spm1mb <- calcSpm(hsSampleData, hsMirrorLocs)
spm4mb <- calcSpm(hsSampleData, hsMirrorLocs, sigma=4000000)

plot(spm1mb)
plot(spm1mb, chromosomes=c(1,5,6,'X'))

siglevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3)
siglevel4mb <- findSigLevelTrad(hsSampleData, spm4mb, n=3)

plot(spm1mb, sig.level=siglevel1mb)

plotScaleSpace(list(spm1mb, spm4mb), list(siglevel1mb, siglevel4mb), type='g')

sigSegments1mb <- getSigSegments(spm1mb, siglevel1mb)
\end{ExampleCode}
\end{Examples}

