\name{"FCS-class"}
\docType{class}
\alias{"FCS"}
\alias{FCS-class}
\alias{FCS}
\alias{"FCS-class"}


\alias{[,FCS-method}
\alias{[<-,FCS-method}
\alias{[[,FCS-method}
\alias{[[<-,FCS-method}
\alias{[[<-,FCS, ANY, ANY}
\alias{"[-methods",FCS-method}
\alias{"[<--methods",FCS-method} 
\alias{"[[-methods",FCS-method} 
\alias{"[[<--methods",FCS-method}

\alias{addParameter,FCS,vector-method}
\alias{checkvars,FCS-method}
\alias{coerce,FCS,matrix-method}
\alias{coerce,FCS,data.frame-method}
\alias{coerce,matrix,FCS-method}
\alias{coerce,data.frame,FCS-method}
\alias{dim.FCS,FCS-method}
\alias{equals,FCS,FCS-method}
\alias{fixvars,FCS-method}
\alias{fluors,FCS-method}
\alias{ggobi,FCS-method}
\alias{metaData,FCS-method}
\alias{plot,FCS,missing-method}
\alias{print,FCS-method}
\alias{show,FCS-method}
\alias{summary,FCS-method}

\alias{"addParameter-methods",FCS,vector-method}
\alias{"checkvars-methods",FCS-method}
\alias{"coerce-methods",FCS,matrix-method}
\alias{"coerce-methods",FCS,data.frame-method}
\alias{"coerce-methods",matrix,FCS-method}
\alias{"coerce-methods",data.frame,FCS-method}
\alias{"dim.FCS-methods",FCS-method}
\alias{"equals-methods",FCS,FCS-method}
\alias{"fixvars-methods",FCS-method}
\alias{"fluors-methods",FCS-method}
\alias{"ggobi-methods",FCS-method}
\alias{"metaData-methods",FCS-method}
\alias{"plot-methods",FCS,missing-method}
\alias{"print-methods",FCS-method}
\alias{"show-methods",FCS-method}
\alias{"summary-methods",FCS-method}

\title{Class "FCS" : Flow Cytometry Standard }
\description{ This class represents objects read from raw binary
  Flow Cytometry Standard (FCS) files.  These files contain a data
  portion, consisting of immunofluorescence and other column variables
  for each cell or row observation, and a metadata portion, which
  contains information such as parameter shortnames, longnames, ranges
  and data dimensions as well as file information. }
\section{Objects from the Class}{
Objects can be created by calls of the form \code{new("FCS", ...)}.
    
}
\section{Slots}{
  \describe{
    \item{\code{data}:}{Object of class \code{"matrix"} which holds
      integer data such that the columns are the variables (usually
      immunofluorescence measurements) and the rows are the cell
      observations. }
    
    \item{\code{metadata}:}{Object of class \code{"FCSmetadata"} which
      holds information about the file, data, and column variables among
      other items in the header of the original raw FCS binary file.}
    
  }
}
\section{Methods}{
  \describe{
    \item{"["}{\code{signature(x = "FCS")}: Extracts the data}
    
    \item{"[<-"}{\code{signature(x = "FCS")}: Replaces or sets the data}
    
    \item{"[["}{\code{signature(x = "FCS")}: Extracts the metadata }
    
    \item{"[[<-"}{\code{signature(x = "FCS")}: Replaces or sets the
      metadata }
    
    \item{addParameter}{\code{signature(x = "FCS", colvar = "vector")}:
      Adds a column parameter to the data }
    
    \item{checkvars}{\code{signature(x = "FCS")}: Checks the
      compatibility of the metadata against the data dimensions and
      column/parameter names and ranges }
    
    \item{coerce}{\code{signature(from = "FCS", to = "matrix")}: Returns
      the data as a matrix}
    
    \item{coerce}{\code{signature(from = "FCS", to = "data.frame")}:
      Returns the data as a data.frame }
    
    \item{coerce}{\code{signature(from = "matrix", to = "FCS")}: Returns
      an FCS object with data and default prototype metadata}
    
    \item{coerce}{\code{signature(from = "data.frame", to = "FCS")}: Returns
      an FCS object with data and default prototype metadata }

    \item{dim.FCS}{\code{signature(x = "FCS")} : Returns the dimensions
      (ie, the number of rows and columns respectively) of the data
      matrix; the output is a vector }
    
    \item{equals}{\code{signature(x = "FCS", y = "FCS")}: Compares the
      equality of two objects in terms of data and metadata
      correspondence }
    
    \item{fixvars}{\code{signature(x = "FCS")}: Sets the discrepant
      metadata slots to values in from the data }
    
    \item{fluors}{\code{signature(x = "FCS")}: Returns the complete data
      portion of the object}
 
    
    \item{metaData}{\code{signature(x = "FCS")}: Returns the complete
      metadata portion of the object }
    
    \item{"plot-methods"}{\code{signature(x = "FCS", y = "missing")}: Plots the
      object as a pairs plot (with rectangular binned contour-image plots or
      hexagonal binned image plots) or as a joint or marginal image
      parallel coordinates plot}

    
    \item{"print-methods"}{\code{signature(x = "FCS")}: Prints a brief description
    about the original filename, dimensions of the data, and the
    original status of the current object's data}
  
    \item{"show-methods"}{\code{signature(object = "FCS")}: Prints a brief description
    about the original filename, dimensions of the data, and the
    original status of the current object's data }
  
    \item{"summary-methods"}{\code{signature(object = "FCS")}: Summaries the
      data's dimensions, five-number summaries on the column parameters,
      the information contained in the metadata}
    
  }
}

\references{
  Trevor Hastie, Robert Tibshirani, and Jerome Friedman. The
  Elements of Statistical Learning: Data Mining, Inference, and
  Prediction. Springer Series in Statistics : New York, 2001. pp.279-283.

  Jerome H. Friedman and Nicholas I. Fisher. Bump Hunting in
  High-Dimensional Data. Tech Report. October 28, 1998.

  J. Paul Robinson, et al. Current Protocols in Cytometry.  John Wiley
  \& Sons, Inc : 2001.

  Mario Roederer and Richard R. Hardy. Frequency Difference Gating: A
  Multivariate Method for Identifying Subsets that Differe between
  Samples. Cytometry, 45:56-64, 2001.

  Mario Roederer and Adam Treister and Wayne Moore and Leonore
  A. Herzenberg. Probability Binning Comparison: A Metric for
  Quantitating Univariate Distribution Differences. Cytometry, 45:37-46,
  2001.

  Keith A. Baggerly. Probability Binning and Testing Agreement between
  Multivariate Immunofluorescence Histograms: Extending the Chi-Squared
  Test. Cytometry, 45:141-150, 2001.
  
}

\author{A.J. Rossini, J.Y. Wan, and Zoe Moodie}

\note{The function \code{read.FCS} is used to read in a raw binary FCS
  files and output a \link{"FCS-class"} object.}

\seealso{
  \code{\link{read.FCS}},
  \code{\link{"FCSgate-class"}},
  \code{\link{"FCSsummary-class"}},
  \code{\link{"FCSmetadata-class"}},
  \code{\link{"plot-methods"}},
  \code{\link{"print-methods"}},
  \code{\link{"show-methods"}},
  \code{\link{"summary-methods"}},
  \code{\link{"coerce-methods"}},
  \code{\link{"[-methods"}},
  \code{\link{"[[-methods"}},
  \code{\link{"[<--methods"}},
  \code{\link{"[[<--methods"}},
  \code{\link{checkvars}},
  \code{\link{fixvars}},
  \code{\link{equals}}, 
  \code{\link{addParameter}}, 
  \code{\link{fluors}},
  \code{\link{metaData}}, 
  \code{\link{dim.FCS}}
}
\examples{

## a default FCS object
default.FCSobj<-new("FCS")

## making my own FCS object
## first making up the data
dummy.data<-matrix(1:1000, ncol=10)
colnames(dummy.data)<-paste("foo", 1:10, sep="")

## second making up the metadata
##   default FCSmetadata
dummy.metadata<-new("FCSmetadata")
##   user-defined metadata
foo.metadata<-new("FCSmetadata", mode="none", size=100, nparam=10,
shortnames=paste("V", 1:10, sep=""), longnames=colnames(dummy.data),
paramranges=unlist(apply(dummy.data, 2, max)), filename="",
objectname="foo.FCSobj", fcsinfo=list("extraInfo1"="dummy FCS",
"extraInfo2"=9:20))

foo.FCSobj<-new("FCS", data=dummy.data, metadata=foo.metadata)

dummy.FCSobj<-new("FCS", data=matrix(), metadata=dummy.metadata)


## extraction of the metadata
foo.FCSobj[["size"]]
## replacement of the metadata
 ## introduce an error in the column length
foo.FCSobj[["nparam"]]<-0

## extraction of the data

first.ten.obs<-foo.FCSobj[1:10,]
## replacement of the data
foo.FCSobj[1:10,]<-matrix(1:100, ncol=10)
## addParameter
foo.FCSobj<-addParameter(foo.FCSobj, 1:100, shortname="newvar",
longname="newlymadevariable", use.shortname=FALSE)

## replacement of the metadata
 ## introduce an error in the column length
foo.FCSobj[["nparam"]]<-0

## checkvars
correct.status.is.FALSE<-checkvars(foo.FCSobj)
## coerce FCS to matrix
coerced.mat<-as(foo.FCSobj, "matrix")
is(coerced.mat, "matrix")
## coerce FCS to data.frame
coerced.df<-as(foo.FCSobj, "data.frame")
is(coerced.df, "data.frame")
## coerce matrix to FCS
FCSobj1<-as(coerced.mat, "FCS")
is(FCSobj1, "FCS")
## coerce data.frame to FCS
FCSobj2<-as(coerced.df, "FCS")
is(FCSobj2, "FCS")

##obtaining the dimensions of the data
dim.FCS(FCSobj2)

## equals

## should be TRUE
equals(FCSobj1, FCSobj2, check.filename=TRUE, check.objectname=TRUE)

## default does not check filename or objectname equality
## should be FALSE
equals(foo.FCSobj, dummy.FCSobj)

## fixvars
foo.FCSobj<-fixvars(foo.FCSobj)
## fluors
data.mat<-fluors(foo.FCSobj)
## metaData
metadata.ls<-metaData(foo.FCSobj)
## plot
## not interesting to plot dummy data

## default plot is pairs.CSP <pairs plot with Contour-images>
## plot(foo.FCSobj)

## can do joint image.parallel.coordinates pairs plots
## plot(foo.FCSobj, image.parallel.plot=TRUE)

## can do marginal image parallel coordinates pairs plots
## plot(foo.FCSobj, image.parallel.plot=TRUE, joint=FALSE)

## print
print(foo.FCSobj)
foo.FCSobj

## show
show(foo.FCSobj)

## summary
summary(foo.FCSobj)
summary(dummy.FCSobj)
}
\keyword{classes}