\name{crlmmIllumina} \alias{crlmmIllumina} \title{Genotype Illumina Infinium II BeadChip data with CRLMM} \description{ This implementation of the CRLMM is especially designed for data from Illumina Infinium II BeadChips. } \usage{ crlmmIllumina(RG, XY, stripNorm=TRUE, useTarget=TRUE, row.names=TRUE, col.names=TRUE, probs=c(1/3, 1/3, 1/3), DF=6, SNRMin=5, gender=NULL, seed=1, save.it=FALSE, load.it=FALSE, intensityFile, mixtureSampleSize=10^5, eps=0.1, verbose=TRUE, cdfName, sns, recallMin=10, recallRegMin=1000, returnParams=FALSE, badSNP=0.7) } \arguments{ \item{RG}{\code{NChannelSet} containing R and G bead intensities} \item{XY}{\code{NChannelSet} containing X and Y bead intensities} \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{row.names}{'logical'. Use rownames - SNP names?} \item{col.names}{'logical'. Use colnames - Sample names?} \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{gender}{'integer' vector, with same length as 'filenames', defining sex. (1 - male; 2 - female)} \item{seed}{'integer' scalar for random number generator (used to sample \code{mixtureSampleSize} SNPs for mixture model.} \item{save.it}{'logical'. Save preprocessed data?} \item{load.it}{'logical'. Load preprocessed data to speed up analysis?} \item{intensityFile}{'character' with filename of preprocessed data to be saved/loaded.} \item{mixtureSampleSize}{'integer'. The number of SNP's to be used when fitting the mixture model.} \item{eps}{Minimum change for mixture model.} \item{verbose}{'logical'.} \item{cdfName}{'character' defining the chip annotation (manifest) to use ('human370v1c', human550v3b', 'human650v3a', 'human1mv1c', 'human370quadv3c', 'human610quadv1b', 'human660quadv1a' 'human1mduov3b')} \item{sns}{'character' vector with sample names to be used.} \item{recallMin}{'integer'. Minimum number of samples for recalibration.} \item{recallRegMin}{'integer'. Minimum number of SNP's for regression.} \item{returnParams}{'logical'. Return recalibrated parameters.} \item{badSNP}{'numeric'. Threshold to flag as bad SNP (affects batchQC)} } \value{ A \code{SnpSet} object which contains \item{calls}{Genotype calls (1 - AA, 2 - AB, 3 - BB)} \item{callProbability}{confidence scores 'round(-1000*log2(1-p))'} in the \code{assayData} slot and \item{SNPQC}{SNP Quality Scores} \item{batchQC}{Batch Quality Scores} along with center and scale parameters when \code{returnParams=TRUE} in the \code{featureData} slot. } \details{ Note: The user should specify either the \code{RG} or \code{XY} intensities, not both. Alternatively if \code{crlmmIllumina} has been run already with \code{save.it=TRUE}, the preprocessed data can be loaded from file by specifying \code{load.it=TRUE} and \code{intensityFile} (\code{RG} or \code{XY} are not needed in this case). } \references{ 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 B, Louis TA, Irizarry RA. Describing Uncertainty in Genome-wide Genotype Calling. (in prep) } \author{Matt Ritchie} \examples{ ## crlmmOut = crlmmIllumina(RG) } \keyword{classif}