Preprocessing and genotyping of Illumina Infinium II arrays.
	Preprocessing and genotyping of Illumina Infinium II arrays.
genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",
      arrayInfoColNames=list(barcode="SentrixBarcode_A", position="SentrixPosition_A"),
      highDensity=FALSE, sep="_", fileExt=list(green="Grn.idat", red="Red.idat"),
      cdfName, copynumber=TRUE, batch, outdir=".", saveDate=TRUE, stripNorm=TRUE, useTarget=TRUE, 
      mixtureSampleSize=10^5, fitMixture=TRUE, eps =0.1, verbose = TRUE, seed = 1, 
      sns, probs = rep(1/3, 3), DF = 6, SNRMin = 5, recallMin = 10, recallRegMin = 1000,
      gender = NULL, returnParams = TRUE, badSNP = 0.7)
  \item{sampleSheet}{\code{data.frame} containing Illumina sample sheet
    information (for required columns, refer to BeadStudio Genotyping
    guide - Appendix A).}
  \item{arrayNames}{character vector containing names of arrays to be
    read in.  If \code{NULL}, all arrays that can be found in the
    specified working directory will be read in.}
  \item{ids}{vector containing ids of probes to be read in.  If
    \code{NULL} all probes found on the first array are read in.}
  \item{path}{character string specifying the location of files to be
    read by the function}
  \item{arrayInfoColNames}{(used when \code{sampleSheet} is specified)
    list containing elements 'barcode' which indicates column names in
    the \code{sampleSheet} which contains the arrayNumber/barcode number
    and 'position' which indicates the strip number.  In older style
    sample sheets, this information is combined (usually in a column
    named 'SentrixPosition') and this should be specified as
    \code{list(barcode=NULL, position="SentrixPosition")}}
  \item{highDensity}{logical (used when \code{sampleSheet} is
    specified). If \code{TRUE}, array extensions '\_A', '\_B' in
    sampleSheet are replaced with 'R01C01', 'R01C02' etc.}
  \item{sep}{character string specifying separator used in .idat file
  \item{fileExt}{list containing elements 'Green' and 'Red' which
    specify the .idat file extension for the Cy3 and Cy5 channels.}
  \item{cdfName}{ annotation package  (see also \code{validCdfNames})}
  \item{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.} 
  \item{batch}{ batch variable. See details. }
  \item{outdir}{character string specifying the location to store large data objects.}
  \item{saveDate}{'logical'.  Should the dates from each .idat be saved
    with sample information?}
  \item{stripNorm}{'logical'.  Should the data be strip-level normalized?}
  \item{useTarget}{'logical' (only used when \code{stripNorm=TRUE}).
    Should the reference HapMap intensities be used in strip-level normalization?}
  \item{mixtureSampleSize}{ Sample size to be use when fitting the mixture model.}
  \item{fitMixture}{ 'logical.' Whether to fit per-array mixture model.}
  \item{eps}{   Stop criteria.}
  \item{verbose}{  'logical.'  Whether to print descriptive messages during processing.}
  \item{seed}{ Seed to be used when sampling. Useful for reproducibility}
  \item{sns}{The sample identifiers.  If missing, the default sample names are \code{basename(filenames)}}
  \item{probs}{'numeric' vector with priors for AA, AB and BB.}
  \item{DF}{'integer' with number of degrees of freedom to use with t-distribution.}
  \item{SNRMin}{'numeric' scalar defining the minimum SNR used to filter
  out samples.}
  \item{recallMin}{Minimum number of samples for recalibration. }
  \item{recallRegMin}{Minimum number of SNP's for regression.}
  \item{gender}{  integer vector (  male = 1, female =2 ) or missing,
  with same length as filenames.  If missing, the gender is predicted.}
  \item{returnParams}{'logical'. Return recalibrated parameters from crlmm.}
  \item{badSNP}{'numeric'. Threshold to flag as bad SNP (affects batchQC)}


	For large datasets it is important to utilize the large data
	support by installing and loading the ff package before calling
	the \code{genotype} function. In previous versions of the
	\code{crlmm} package, we useed different functions for
	genotyping depending on whether the ff package is loaded, namely
	\code{genotype} and \code{genotype2}.  The \code{genotype}
	function now handles both instances.

	\code{genotype.Illumina} is a wrapper of the \code{crlmm}
	function for genotyping.  Differences include (1) that the copy
	number probes (if present) are also quantile-normalized and (2)
	the class of object returned by this function, \code{CNSet}, is
	needed for subsequent copy number estimation.  Note that the
	batch variable that must be passed to this function has no
	effect on the normalization or genotyping steps.  Rather,
	\code{batch} is required in order to initialize a \code{CNSet}
	container with the appropriate dimensions.

\value{	A \code{SnpSuperSet} instance.}
  Ritchie ME, Carvalho BS, Hetrick KN, Tavar\'{e} S, Irizarry RA.
  R/Bioconductor software for Illumina's Infinium whole-genome 
  genotyping BeadChips. Bioinformatics. 2009 Oct 1;25(19):2621-3.

  Carvalho B, Bengtsson H, Speed TP, Irizarry RA. Exploration,
  normalization, and genotype calls of high-density oligonucleotide SNP
  array data. Biostatistics. 2007 Apr;8(2):485-99. Epub 2006 Dec
  22. PMID: 17189563.

  Carvalho BS, Louis TA, Irizarry RA.
  Quantifying uncertainty in genotype calls.
  Bioinformatics. 2010 Jan 15;26(2):242-9.

\author{Matt Ritchie}
\note{For large datasets, load the 'ff' package prior to genotyping --
this will greatly reduce the RAM required for big jobs.  See
\code{ldPath} and \code{ocSamples}.}