\name{SPADE.markerMedians}
\alias{SPADE.markerMedians}
\alias{SPADE.annotateMarkers}
\title{
Compute marker medians, coefficient of variations and counts for clusters
}
\description{
Compute the marker medians, coefficients of variation and observations counts for cluster annoated FCS files.
}
\usage{
SPADE.markerMedians(files, num.clusters, cols = NULL, arcsinh_cofactor = 5, cluster_cols=NULL, comp=TRUE)
SPADE.annotateMarkers(files, cols = NULL, arcsinh_cofactor = 5)
}
\arguments{
  \item{files}{
Name of input FCS file or vector of input FCS file names. FCS files must have "cluster" column.
}
  \item{num.clusters}{
Number of clusters. Note not all clusters need to be present in all files.
  }
  \item{cols}{
Usually a vector of strings specifying the columns to be used in the density
calculation, e.g., c("(Cd110)D","(Cs111)D"). Strings will be matched against
the parameter names extracted from the FCS file. The default=NULL will
use all parameters. 
}
  \item{arcsinh_cofactor}{
Cofactor used in the arcsinh transform \code{asinh(data/arcsinh_cofactor)} of data
}
  \item{cluster_cols}{
A vector of strings specifying columns that should be marked as having been used in clustering
}
  \item{comp}{
Apply compensation matrix if present in SPILL or SPILLOVER keywords
}
}
\details{
SPADE.annotateMarkers is deprecated.
}
\value{
List with:
\item{count}{Matrix of observation count for clusters}
\item{percenttotal}{Matrix of percent of total number of cells [0-100] in each cluster}
\item{medians}{Matrix of medians for specified columns}
\item{cvs}{Matrix of coefficient of variation (CV), 100*sd(data)/abs(mean(data)), for specified columns}
}
\author{
Michael Linderman
}
\seealso{
\code{\link{SPADE.addClusterToFCS}}, \code{\link{SPADE.annotateGraph}}
}
\examples{
	# Not run
	## Load two-parameters sample data included in package
	#data_file_path = paste(installed.packages()["spade","LibPath"],"spade","extdata","SimulatedRawData.fcs",sep=.Platform$file.sep)

	## Run basic SPADE analyses, clustering on two parameters. 
	#output_dir <- tempdir()
	#SPADE.driver(data_file_path, out_dir=output_dir, cluster_cols=c("marker1","marker2"))

	## Compute medians, counts and other parameters from processed files
	#upsampled_file_path <- paste(output_dir,.Platform$file.sep,basename(data_file_path),".density.fcs.cluster.fcs",sep="")
	#mst_graph <- igraph:::read.graph(paste(output_dir,"mst.gml",sep=.Platform$file.sep),format="gml")
	#anno <- SPADE.markerMedians(upsampled_file_path, igraph:::vcount(mst_graph), cols = c("marker1","marker2"))
}