\HeaderA{qscores}{Examples of qscore objects (quality scores) to apply to CGH arrays}{qscores}
\aliasA{clone.qscore}{qscores}{clone.qscore}
\aliasA{dyn.x.qscore}{qscores}{dyn.x.qscore}
\aliasA{dyn.y.qscore}{qscores}{dyn.y.qscore}
\aliasA{dynamics.qscore}{qscores}{dynamics.qscore}
\aliasA{pct.clone.qscore}{qscores}{pct.clone.qscore}
\aliasA{pct.replicate.qscore}{qscores}{pct.replicate.qscore}
\aliasA{pct.spot.before.qscore}{qscores}{pct.spot.before.qscore}
\aliasA{pct.spot.qscore}{qscores}{pct.spot.qscore}
\aliasA{smoothness.qscore}{qscores}{smoothness.qscore}
\aliasA{var.replicate.qscore}{qscores}{var.replicate.qscore}
\keyword{datasets}{qscores}
\begin{Description}\relax
This data set provides \code{\LinkA{qscore}{qscore}} objects that can be
applied to \emph{normalized} \code{arrayCGH} objects in order to
evaluate data quality after normalization.
\end{Description}
\begin{Usage}
\begin{verbatim}data(qscores)\end{verbatim}
\end{Usage}
\begin{Format}\relax
The following \code{qscore} objects are provided:
\Tabular{lll}{
& \code{clone.qscore} & number of clones \\
& \code{pct.clone.qscore} & percentage of clones \\
& \code{pct.spot.qscore} & percentage of spots \\
& \code{pct.spot.before.qscore} & percentage of spots before normalization\\
& \code{pct.replicate.qscore} & average percentage of replicates \\
& \code{smoothness.qscore} & signal smoothness\\
& \code{var.replicate.qscore} & \\
& \code{dyn.x.qscore} & signal dynamics on X chromosome\\
& \code{dyn.y.qscore} & signal dynamics on Y chromosome\\
}
\end{Format}
\begin{Note}\relax
People interested in tools for array-CGH analysis can
visit our web-page: \url{http://bioinfo.curie.fr}.
\end{Note}
\begin{Author}\relax
Pierre Neuvial, \email{manor@curie.fr}.
\end{Author}
\begin{Source}\relax
Institut Curie, \email{manor@curie.fr}.
\end{Source}
\begin{SeeAlso}\relax
\code{\LinkA{spatial}{spatial}}, \code{\LinkA{qscore.summary.arrayCGH}{qscore.summary.arrayCGH}},
\code{\LinkA{qscore}{qscore}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(qscores)
data(spatial)

## define a list of qscores
qscore.list <- list(clone=clone.qscore, pct.clone=pct.clone.qscore,
pct.spot=pct.spot.qscore, pct.replicate=pct.replicate.qscore,
smoothness=smoothness.qscore, dyn.x=dyn.x.qscore, dyn.y=dyn.y.qscore,
var.replicate=var.replicate.qscore)

## compute quality scores for a couple of normalized arrays
gradient.norm$quality <- qscore.summary.arrayCGH(gradient.norm,
qscore.list)
print(gradient.norm$quality[, 2:3])

qscore.list$dyn.x$args$test <- 23
qscore.list$dyn.y$args$test <- 24
edge.norm$quality <- qscore.summary.arrayCGH(edge.norm, qscore.list)
print(edge.norm$quality[, 2:3])
\end{ExampleCode}
\end{Examples}

