\name{snprma}
 \Rdversion{1.1}
 \alias{snprma}

 \alias{snprma2}

 
 \title{
   Preprocessing tool for SNP arrays.
 }
 \description{
   SNPRMA will preprocess SNP chips. The preprocessing consists of
   quantile normalization to a known target distribution and

   summarization to the SNP-Allele level.

 }
 \usage{

 snprma(filenames, mixtureSampleSize = 10^5, fitMixture = FALSE, eps = 0.1, verbose = TRUE, seed = 1, cdfName, sns)

 snprma2(filenames, mixtureSampleSize = 10^5, fitMixture = FALSE, eps = 0.1, verbose = TRUE, seed = 1, cdfName, sns)

 }
 \arguments{
   \item{filenames}{
     'character' vector with file names.
 }
   \item{mixtureSampleSize}{
     Sample size to be use when fitting the mixture model.
 }
   \item{fitMixture}{
     'logical'. Fit the mixture model?
 }
   \item{eps}{
     Stop criteria.
 }
   \item{verbose}{
     'logical'.
 }
   \item{seed}{
     Seed to be used when sampling.
 }
   \item{cdfName}{

     cdfName: 'GenomeWideSnp\_5', 'GenomeWideSnp\_6'
 }
   \item{sns}{
     Sample names.

 }
 }
 \value{
   \item{A}{Summarized intensities for Allele A}
   \item{B}{Summarized intensities for Allele B}
   \item{sns}{Sample names}
   \item{gns}{SNP names}
   \item{SNR}{Signal-to-noise ratio}
   \item{SKW}{Skewness}
   \item{mixtureParams}{Parameters from mixture model}
   \item{cdfName}{Name of the CDF}
 }

 \details{
   'snprma2' allows one to genotype very large datasets (via ff package) and also permits
   the use of clusters or multiple cores (via snow package) to speed up preprocessing.
   }

 \examples{

 if (require(genomewidesnp6Crlmm) & require(hapmapsnp6) & require(oligoClasses)){
   path <- system.file("celFiles", package="hapmapsnp6")

 
   ## the filenames with full path...
   ## very useful when genotyping samples not in the working directory
   cels <- list.celfiles(path, full.names=TRUE)

   snprmaOutput <- snprma(cels)
   snprmaOutput[["A"]][1:10,]
   snprmaOutput[["B"]][1:10,]

 }

 \dontrun{
 ## HPC Example
 library(ff)
 library(snow)
 library(crlmm)
 ## genotype 50K SNPs at a time
 ocProbesets(50000)
 ## setup cluster - 8 cores on the machine
 setCluster(8, "SOCK")
 

 path <- system.file("celFiles", package="hapmapsnp6")

 cels <- list.celfiles(path, full.names=TRUE)
 snprmaOutput <- snprma2(cels)
 
 }
 

 }
 \keyword{manip}
 \keyword{classif}