\HeaderA{callFilter-methods}{Detection Call Filter}{callFilter.Rdash.methods}
\aliasA{callFilter}{callFilter-methods}{callFilter}
\aliasA{callFilter<\Rdash}{callFilter-methods}{callFilter<.Rdash.}
\keyword{methods}{callFilter-methods}
\begin{Description}\relax
Detection Call Filter. \\
The \code{cutoff} value defines the upper threshold for allowed detection call p-values. If e.g.
the number of samples exceeding this cutoff value is greater than \code{samples} then the
corresponding expression dataframe row is flagged, i.e. \code{flag = 0}. \\
The Detection Call Filter flags all rows with: \code{flag = (sum(call[i] >= cutoff) >= samples)}

\emph{Usage}

\code{callFilter(object)} \\
\code{callFilter(object, value)<-}
\end{Description}
\begin{Arguments}
\begin{ldescription}
\item[\code{object}] object of class \code{PreFilter} or \code{UniFilter}.
\item[\code{value}] character vector \code{c(cutoff, samples, condition)}.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
The method \code{callFilter} initializes the following parameters:
\Tabular{lll}{
& \code{cutoff}:& the cutoff value for the filter: \\
&               & \code{cutoff = 1.0}: present/absent call is used. \\
&               & \code{cutoff < 1.0}: detection p-value is used as cutoff. \\
& \code{samples}:& this value depends on the \code{condition} used: \\
& \code{condition}:& \code{condition="samples"}: number of samples (default): \\
&                  & \code{condition="percent"}: percent of samples.
}
\end{Details}
\begin{Value}
An initialized \code{\LinkA{PreFilter}{PreFilter.Rdash.class}} or \code{\LinkA{UniFilter}{UniFilter.Rdash.class}} object.
\end{Value}
\begin{Author}\relax
Christian Stratowa
\end{Author}
\begin{Examples}
\begin{ExampleCode}
## initialize PreFilter
prefltr <- PreFilter()
callFilter(prefltr) <- c(0.02,80.0,"percent")
str(prefltr)

## initialize UniFilter
unifltr <- UniFilter()
callFilter(unifltr) <- c(0.02,80.0,"percent")
str(unifltr)
\end{ExampleCode}
\end{Examples}

