\HeaderA{SAM-class}{Class SAM}{SAM.Rdash.class}
\aliasA{identify,SAM-method}{SAM-class}{identify,SAM.Rdash.method}
\aliasA{plot,SAM-method}{SAM-class}{plot,SAM.Rdash.method}
\aliasA{print,SAM-method}{SAM-class}{print,SAM.Rdash.method}
\aliasA{SAM}{SAM-class}{SAM}
\aliasA{show,SAM-method}{SAM-class}{show,SAM.Rdash.method}
\aliasA{summary,SAM-method}{SAM-class}{summary,SAM.Rdash.method}
\keyword{classes}{SAM-class}
\begin{Description}\relax
This is a class representation for several versions of the
SAM (Significance Analysis of Microarrays) procedure proposed by Tusher
et al. (2001).
\end{Description}
\begin{Section}{Objects from the Class}
Objects can be created using the functions \code{sam}, \code{sam.dstat}, 
\code{sam.wilc} and \code{sam.snp}.
\end{Section}
\begin{Section}{Slots}
\describe{
\item[\code{d}:] Object of class \code{"numeric"} representing the
expression scores of the genes.
\item[\code{d.bar}:] Object of class \code{"numeric"} representing
the expected expression scores under the null hypothesis.
\item[\code{vec.false}:] Object of class \code{"numeric"} containing
the one-sided expected number of falsely called genes
\item[\code{p.value}:] Object of class \code{"numeric"} consisting of
the p-values of the genes
\item[\code{s}:] Object of class \code{"numeric"} representing the
standard deviations of the genes. If the standard deviations are
not computed, \code{s} will be set to \code{numeric(0)}. 
\item[\code{s0}:] Object of class \code{"numeric"} representing the
value of the fudge factor. If not computed, \code{s0} will be
set to \code{numeric(0)}.
\item[\code{mat.samp}:] Object of class \code{"matrix"} containing
the permuted group labels used in the estimation of the null
distribution. Each row represents one permutation, each column
one observation (pair). If no permutation procedure has been used,
\code{mat.samp} will be set to \code{matrix(numeric(0))}.
\item[\code{p0}:] Object of class \code{"numeric"} representing the
prior probability that a gene is not differentially expressed.
\item[\code{mat.fdr}:] Object of class \code{"matrix"} containing general
information as the number of significant genes and the estimated FDR
for several values of \eqn{\Delta}{Delta}. Each row represents one
value of \eqn{\Delta}{Delta}, each of the 9 columns one statistic.
\item[\code{q.value}:] Object of class \code{"numeric"} consisting of
the q-values of the genes. If not computed, \code{q.value} will be
set to \code{numeric(0)}.
\item[\code{fold}:] Object of class \code{"numeric"} representing the
fold changes of the genes. If not computed, \code{fold} will be 
set to \code{numeric(0)}.
\item[\code{msg}:] Object of class \code{"character"} containing information
about, e.g., the type of analysis. \code{msg} is printed when the functions
\code{print} and \code{summary}, respectively, are called.
\item[\code{chip}:] Object of class \code{"character"} naming the microarray
used in the analysis. If no information about the chip is available,
\code{chip} will be set to \code{""}.
}
\end{Section}
\begin{Section}{Methods}
\describe{
\item[identify] \code{signature(x = "SAM")}: After generating a SAM plot,
\code{identify} can be used to obtain information about the genes by
clicking on the symbols in the SAM plot. For details, see 
\code{help.sam(identify)}. Arguments are listed by \code{args.sam(identify)}.
\item[plot] \code{signature(x = "SAM")}: Generates a SAM plot or the Delta
plots. If the specified \code{delta} in \code{plot(object,delta)} is
a numeric value, a SAM plot will be generated. If \code{delta} is either
not specified or a numeric vector, the Delta plots will be generated.
For details, see \code{?sam.plot2}, \code{?delta.plot} or 
\code{help.sam(plot)},respectively. Arguments are listed by \code{args.sam(plot)}.
\item[print] \code{signature(x = "SAM")}: Prints general information such as 
the number of significant genes and the estimated FDR for a set of 
\eqn{\Delta}{Delta}. For details, see \code{help.sam(print)}. Arguments are
listed by \code{args.sam(print)}.
\item[show] \code{signature(object = "SAM")}: Shows the output of the SAM
analysis.
\item[summary] \code{signature(object = "SAM")}: Summarizes the results of
a SAM analysis. If \code{delta} in \code{summary(object,delta)} is not
specified or a numeric vector, the information shown by print and some
additional information will be shown. If \code{delta} is a numeric
vector, the general information for the specific \eqn{\Delta}{Delta} is
shown and additionally gene-specific information about the genes called 
significant using this value of \eqn{\Delta}{Delta}. The output of summary
is an object of class sumSAM which has the slots \code{row.sig.genes},
\code{mat.fdr}, \code{mat.sig} and \code{list.args}. For details, 
see \code{help.sam(summary)}. All arguments are listed by \code{args.sam(summary)}.
}
\end{Section}
\begin{Note}\relax
SAM was developed by Tusher et al. (2001).

!!! There is a patent pending for the SAM technology at Stanford University. !!!
\end{Note}
\begin{Author}\relax
Holger Schwender, \email{holger.schw@gmx.de}
\end{Author}
\begin{References}\relax
Schwender, H., Krause, A. and Ickstadt, K. (2003). Comparison of
the Empirical Bayes and the Significance Analysis of Microarrays.
\emph{Technical Report}, SFB 475, University of Dortmund, Germany.
\url{http://www.sfb475.uni-dortmund.de/berichte/tr44-03.pdf}.

Schwender, H. (2004). Modifying Microarray Analysis Methods for 
Categorical Data -- SAM and PAM for SNPs. To appear in: \emph{Proceedings
of the the 28th Annual Conference of the GfKl}.

Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance analysis of microarrays
applied to the ionizing radiation response. \emph{PNAS}, 98, 5116-5121.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{sam}{sam}},\code{\LinkA{sam.dstat}{sam.dstat}},\code{\LinkA{sam.wilc}{sam.wilc}},
\code{\LinkA{sam.snp}{sam.snp}},\code{\LinkA{args.sam}{args.sam}},\code{\LinkA{sam.plot2}{sam.plot2}},
\code{\LinkA{delta.plot}{delta.plot}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}## Not run: 
  # Load the package multtest and the data of Golub et al. (1999)
  # contained in multtest.
  library(multtest)
  data(golub)
  
  # Perform a SAM analysis for the two class unpaired case assuming
  # unequal variances.
  sam.out<-sam(golub,golub.cl,B=100,rand=123)
  sam.out
  
  # Alternative ways to show the output of sam.
  show(sam.out)
  print(sam.out)
  
  # Obtain a little bit more information.
  summary(sam.out)
  
  # Print the results of the SAM analysis for other values of Delta.
  print(sam.out,seq(.2,2,.2))
  
  # Again, the same with additional information.
  summary(sam.out,seq(.2,2,.2))
    
  # Obtain the Delta plots for the default set of Deltas.
  plot(sam.out)
  
  # Generate the Delta plots for Delta = 0.2, 0.4, 0.6, ..., 2.
  plot(sam.out,seq(0.2,0.4,2))
  
  # Obtain the SAM plot for Delta = 2.
  plot(sam.out,2)
  
  # Get information about the genes called significant using 
  # Delta = 3 (since neither the gene names nor the chip type
  # has been specified ll is set to FALSE to avoid a warning).
  sam.sum3<-summary(sam.out,3,ll=FALSE)
  sam.sum3
  
  # Obtain the rows of the Golub et al. (1999) data set containing
  # the genes called differentially expressed
  sam.sum3@row.sig.genes
  
  # and their names
  golub.gnames[sam.sum3@row.sig.genes,3] 

  # The matrix containing the d-values, q-values etc. of the
  # differentially expressed genes can be obtained by
  sam.out@mat.sig
## End(Not run)\end{ExampleCode}
\end{Examples}