@@ -1,5 +1,6 @@

 \name{genotype.Illumina}

 \alias{genotype.Illumina}

+\alias{crlmmIllumina}

 \title{

 	Preprocessing and genotyping of Illumina Infinium II arrays.

@@ -10,11 +11,20 @@

 \usage{

 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"), XY=NULL,

+      highDensity=FALSE, sep="_", fileExt=list(green="Grn.idat", red="Red.idat"), XY=NULL, anno, genome, 

       call.method="crlmm", trueCalls=NULL, cdfName, copynumber=TRUE, batch=NULL, saveDate=FALSE, stripNorm=TRUE, 

-      useTarget=TRUE, quantile.method="between", mixtureSampleSize=10^5, fitMixture=TRUE,                               

-      eps =0.1, verbose = TRUE, seed = 1, sns, probs = rep(1/3, 3), DF = 6, SNRMin = 5, 

+      useTarget=TRUE, quantile.method="between", nopackage.norm="quantile", 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)

+

+crlmmIllumina(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"), XY=NULL, anno, genome, 

+      call.method="crlmm", trueCalls=NULL, cdfName, copynumber=TRUE, batch=NULL, saveDate=FALSE, stripNorm=TRUE, 

+      useTarget=TRUE, quantile.method="between", nopackage.norm="quantile", 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)

+

 }

 \arguments{

   \item{sampleSheet}{\code{data.frame} containing Illumina sample sheet

@@ -42,9 +52,13 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   \item{fileExt}{list containing elements 'Green' and 'Red' which

     specify the .idat file extension for the Cy3 and Cy5 channels.}

   \item{XY}{\code{NChannelSet} containing X and Y intensities.}

+  \item{anno}{data.frame containing SNP annotation information from 

+    manifest and additional columns 'isSnp', 'position', 'chromosome' 

+    and 'featureNames'. For use when \code{cdfName}='nopackage'}

+  \item{genome}{character string specifying which genome is used in annotation}

   \item{call.method}{character string specifying the genotype calling algorithm to use ('crlmm' or 'krlmm').}

   \item{trueCalls}{matrix specifying known Genotype calls(can contain some NAs) for a subset of samples and features (1 - AA, 2 - AB, 3 - BB).}

-  \item{cdfName}{ annotation package  (see also \code{validCdfNames})}

+  \item{cdfName}{annotation package (see also \code{validCdfNames}) or 'nopackage' when combined with 'krlmm', an \code{anno} data.frame and \code{genome}.}

   \item{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.}

   \item{batch}{ character vector indicating the batch variable. Must be

 	the same length as the number of samples. See details.}

@@ -54,6 +68,8 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   \item{useTarget}{'logical' (only used when \code{stripNorm=TRUE}).

     Should the reference HapMap intensities be used in strip-level normalization?}

   \item{quantile.method}{character string specifying the quantile normalization method to use ('within' or 'between' channels).}

+  \item{nopackage.norm}{character string specifying normalization to be used when \code{cdfName}='nopackage'.

+    Options are 'none', 'quantile' (within channel, between array) and 'loess'.}

   \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.}

@@ -74,23 +90,15 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 \details{

-	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 used 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 (a character string) 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.

+	\code{genotype.Illumina} (or equivalently \code{crlmmIllumina}) 

+        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 (a character string) 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.

         The new 'krlmm' option is available for certain chip types. Optional 

 	argument \code{trueCalls} matrix contains known Genotype calls 

@@ -103,6 +111,15 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	8 clusters. This is configurable by setting up an option named 

 	"krlmm.cores", e.g. options("krlmm.cores" = 16). 

+        In general, a chip specific annotation package is required to use the 

+        \code{genotype.Illumina} function. If this is not available (newer chip 

+        types or custom chips often don't have a chip-specific package available

+        on Bioconductor), consider using \code{cdfName}='nopackage' and specifying 

+        \code{anno} and \code{genome}, which runs 'krlmm' on the samples available.

+        Here \code{anno} is a data.frame read in from the relevant chip-specific

+        manifest, which must have additional columns 'isSnp' which is a logical that

+        indicates whether a probe is polymorphic or not, 'position', 'chromosome' and

+        'featureNames' that give the location on the chromosome and SNP name.

       }

 \value{	A \code{SnpSuperSet} instance.}

@@ -111,6 +128,10 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   R/Bioconductor software for Illumina's Infinium whole-genome

   genotyping BeadChips. Bioinformatics. 2009 Oct 1;25(19):2621-3.

+  Liu R, Dai Z, Yeager M, Irizarry RA1, Ritchie ME.

+  KRLMM: an adaptive genotype calling method for common and low frequency variants.

+  BMC Bioinformatics. 2014 May 23;15:158.

+

   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

@@ -119,19 +140,11 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   Carvalho BS, Louis TA, Irizarry RA.

   Quantifying uncertainty in genotype calls.

   Bioinformatics. 2010 Jan 15;26(2):242-9.

-

 }

 \author{Matt Ritchie, Cynthia Liu, Zhiyin Dai}

-  \note{For large datasets, load the 'ff' package prior to genotyping

-\code{ldPath} and \code{ocSamples}.  The function

-\code{genotype.Illumina} supports parallelization, as the (not run)

-example below indicates.}

-

 \seealso{

-	\code{\link{crlmmIlluminaV2}},

 	\code{\link[oligoClasses]{ocSamples}},

 	\code{\link[oligoClasses]{ldOpts}}

 }

@@ -11,7 +11,7 @@

 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"), XY=NULL,

-      call.method="crlmm", trueCalls=NULL, cdfName, copynumber=TRUE, batch=NULL, saveDate=TRUE, stripNorm=TRUE, 

+      call.method="crlmm", trueCalls=NULL, cdfName, copynumber=TRUE, batch=NULL, saveDate=FALSE, stripNorm=TRUE, 

       useTarget=TRUE, quantile.method="between", 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)

@@ -93,8 +93,16 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	\code{CNSet} container with the appropriate dimensions.

         The new 'krlmm' option is available for certain chip types. Optional 

-	\code{trueCalls} matrix contains known Genotype calls (1 - AA, 2 - AB, 3 - BB)

-	for a subset of samples and features. 

+	argument \code{trueCalls} matrix contains known Genotype calls 

+	(1 - AA, 2 - AB, 3 - BB) for a subset of samples and features. This 

+	will used to compute KRLMM coefficients by calling \code{vglm} function 

+	from \code{VGAM} package.

+

+	The 'krlmm' method makes use of functions provided in \code{parallel} 

+	package to speed up the process. It by default initialises up to 

+	8 clusters. This is configurable by setting up an option named 

+	"krlmm.cores", e.g. options("krlmm.cores" = 16). 

+

       }

 \value{	A \code{SnpSuperSet} instance.}

@@ -114,7 +122,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 }

-\author{Matt Ritchie}

+\author{Matt Ritchie, Cynthia Liu, Zhiyin Dai}

   \note{For large datasets, load the 'ff' package prior to genotyping

 -- this will greatly reduce the RAM required for big jobs.  See

@@ -129,6 +137,7 @@ example below indicates.}

 }

 \examples{

 \dontrun{

+	# example for 'crlmm' option

 	library(ff)

 	library(crlmm)

 	## to enable paralellization, set to TRUE

@@ -151,6 +160,32 @@ example below indicates.}

 				   arrayInfoColNames=arrayInfo,

 				   cdfName="human370v1c",

 				   batch=rep("1", nrow(samplesheet)))

+

+}

+\dontrun{

+	# example for 'krlmm' option

+	library(crlmm)

+	library(ff)

+	# line below is an optional step for krlmm to initialise 16 workers 

+	# options("krlmm.cores" = 16)

+	# read in raw X and Y intensities output by GenomeStudio's GenCall genotyping module

+	XY = readGenCallOutput(c("HumanOmni2-5_4v1_FinalReport_83TUSCAN.csv","HumanOmni2-5_4v1_FinalReport_88CHB-JPT.csv"),

+				cdfName="humanomni25quadv1b",

+				verbose=TRUE)

+	krlmmResult = genotype.Illumina(XY=XY, 

+		      			cdfName=ThiscdfName, 

+					call.method="krlmm", 

+					verbose=TRUE)

+

+	# example for 'krlmm' option with known genotype call for some SNPs and samples

+	library(VGAM)

+	hapmapCalls = load("hapmapCalls.rda")

+	# hapmapCalls should have rownames and colnames corresponding to XY featureNames and sampleNames

+	krlmmResult = genotype.Illumina(XY=XY,

+					cdfName=ThiscdfName, 

+					call.method="krlmm", 

+					trueCalls=hapmapCalls, 

+					verbose=TRUE)		

 }

 }

 \keyword{classif}

old mode 100644

new mode 100755

@@ -11,7 +11,7 @@

 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"), XY=NULL,

-      call.method="crlmm", cdfName, copynumber=TRUE, batch=NULL, saveDate=TRUE, stripNorm=TRUE, 

+      call.method="crlmm", trueCalls=NULL, cdfName, copynumber=TRUE, batch=NULL, saveDate=TRUE, stripNorm=TRUE, 

       useTarget=TRUE, quantile.method="between", 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)

@@ -43,6 +43,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

     specify the .idat file extension for the Cy3 and Cy5 channels.}

   \item{XY}{\code{NChannelSet} containing X and Y intensities.}

   \item{call.method}{character string specifying the genotype calling algorithm to use ('crlmm' or 'krlmm').}

+  \item{trueCalls}{matrix specifying known Genotype calls(can contain some NAs) for a subset of samples and features (1 - AA, 2 - AB, 3 - BB).}

   \item{cdfName}{ annotation package  (see also \code{validCdfNames})}

   \item{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.}

   \item{batch}{ character vector indicating the batch variable. Must be

@@ -65,7 +66,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   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,

+  \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)}

@@ -91,7 +92,9 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	Rather, \code{batch} is required in order to initialize a

 	\code{CNSet} container with the appropriate dimensions.

-        The new 'krlmm' option is available for certain chip types.

+        The new 'krlmm' option is available for certain chip types. Optional 

+	\code{trueCalls} matrix contains known Genotype calls (1 - AA, 2 - AB, 3 - BB)

+	for a subset of samples and features. 

       }

 \value{	A \code{SnpSuperSet} instance.}

@@ -10,11 +10,11 @@

 \usage{

 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, 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)

+      highDensity=FALSE, sep="_", fileExt=list(green="Grn.idat", red="Red.idat"), XY=NULL,

+      call.method="crlmm", cdfName, copynumber=TRUE, batch=NULL, saveDate=TRUE, stripNorm=TRUE, 

+      useTarget=TRUE, quantile.method="between", 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)

 }

 \arguments{

   \item{sampleSheet}{\code{data.frame} containing Illumina sample sheet

@@ -41,6 +41,8 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

     names.}

   \item{fileExt}{list containing elements 'Green' and 'Red' which

     specify the .idat file extension for the Cy3 and Cy5 channels.}

+  \item{XY}{\code{NChannelSet} containing X and Y intensities.}

+  \item{call.method}{character string specifying the genotype calling algorithm to use ('crlmm' or 'krlmm').}

   \item{cdfName}{ annotation package  (see also \code{validCdfNames})}

   \item{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.}

   \item{batch}{ character vector indicating the batch variable. Must be

@@ -50,6 +52,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   \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{quantile.method}{character string specifying the quantile normalization method to use ('within' or 'between' channels).}

   \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.}

@@ -88,8 +91,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	Rather, \code{batch} is required in order to initialize a

 	\code{CNSet} container with the appropriate dimensions.

-

-

+        The new 'krlmm' option is available for certain chip types.

       }

 \value{	A \code{SnpSuperSet} instance.}

@@ -129,8 +129,10 @@ example below indicates.}

 	## to enable paralellization, set to TRUE

 	if(FALSE){

 		library(snow)

-		## 10 workers

-		setCluster(10, "SOCK")

+		library(doSNOW)

+		## with 10 workers

+		cl <- makeCluster(10, type="SOCK")

+		registerDoSNOW(cl)

 	}

 	## path to idat files

 	datadir <- "/thumper/ctsa/snpmicroarray/illumina/IDATS/370k"

@@ -88,6 +88,8 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	Rather, \code{batch} is required in order to initialize a

 	\code{CNSet} container with the appropriate dimensions.

+

+

       }

 \value{	A \code{SnpSuperSet} instance.}

@@ -106,10 +108,14 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   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}.}

+

+  \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}.  The function

+\code{genotype.Illumina} supports parallelization, as the (not run)

+example below indicates.}

 \seealso{

 	\code{\link{crlmmIlluminaV2}},

@@ -117,6 +123,27 @@ this will greatly reduce the RAM required for big jobs.  See

 	\code{\link[oligoClasses]{ldOpts}}

 }

 \examples{

-  ##

+\dontrun{

+	library(ff)

+	library(crlmm)

+	## to enable paralellization, set to TRUE

+	if(FALSE){

+		library(snow)

+		## 10 workers

+		setCluster(10, "SOCK")

+	}

+	## path to idat files

+	datadir <- "/thumper/ctsa/snpmicroarray/illumina/IDATS/370k"

+	## read in your samplesheet

+	samplesheet = read.csv(file.path(datadir, "HumanHap370Duo_Sample_Map.csv"), header=TRUE, as.is=TRUE)

+	samplesheet <- samplesheet[-c(28:46,61:75,78:79), ]

+	arrayNames <- file.path(datadir, unique(samplesheet[, "SentrixPosition"]))

+	arrayInfo <- list(barcode=NULL, position="SentrixPosition")

+	cnSet <- genotype.Illumina(sampleSheet=samplesheet,

+				   arrayNames=arrayNames,

+				   arrayInfoColNames=arrayInfo,

+				   cdfName="human370v1c",

+				   batch=rep("1", nrow(samplesheet)))

+}

 }

 \keyword{classif}

@@ -11,8 +11,8 @@

 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, saveDate=TRUE, stripNorm=TRUE, useTarget=TRUE, 

-      mixtureSampleSize=10^5, fitMixture=TRUE, eps =0.1, verbose = TRUE, seed = 1, 

+      cdfName, copynumber=TRUE, batch, 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)

 }

@@ -42,8 +42,9 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

   \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{copynumber}{ 'logical.' Whether to store copy number intensities with SNP output.}

+  \item{batch}{ character vector indicating the batch variable. Must be

+	the same length as the number of samples. See details.}

   \item{saveDate}{'logical'.  Should the dates from each .idat be saved

     with sample information?}

   \item{stripNorm}{'logical'.  Should the data be strip-level normalized?}

@@ -82,16 +83,17 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	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.

-}

+	batch variable (a character string) 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.}

 \references{

   Ritchie ME, Carvalho BS, Hetrick KN, Tavar\'{e} S, Irizarry RA.

-  R/Bioconductor software for Illumina's Infinium whole-genome 

+  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,

@@ -110,7 +112,7 @@ this will greatly reduce the RAM required for big jobs.  See

 \code{ldPath} and \code{ocSamples}.}

 \seealso{

-	\code{\link{crlmmIlluminaV2}}, 

+	\code{\link{crlmmIlluminaV2}},

 	\code{\link[oligoClasses]{ocSamples}},

 	\code{\link[oligoClasses]{ldOpts}}

 }

@@ -72,7 +72,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

 	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

+	\code{crlmm} package, we used 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.

@@ -11,7 +11,7 @@

 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, 

+      cdfName, copynumber=TRUE, batch, 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)

@@ -43,8 +43,7 @@ genotype.Illumina(sampleSheet=NULL, arrayNames=NULL, ids=NULL, path=".",

     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{batch}{ batch variable. See details.}

   \item{saveDate}{'logical'.  Should the dates from each .idat be saved

     with sample information?}

   \item{stripNorm}{'logical'.  Should the data be strip-level normalized?}

new file mode 100644

@@ -0,0 +1,121 @@

+\name{genotype.Illumina}

+\alias{genotype.Illumina}

+

+\title{

+	Preprocessing and genotyping of Illumina Infinium II arrays.

+}

+\description{

+	Preprocessing and genotyping of Illumina Infinium II arrays.

+}

+\usage{

+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)

+}

+\arguments{

+  \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

+    names.}

+  \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)}

+}

+

+\details{

+

+	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.}

+\references{

+  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}.}

+

+\seealso{

+	\code{\link{crlmmIlluminaV2}}, 

+	\code{\link[oligoClasses]{ocSamples}},

+	\code{\link[oligoClasses]{ldOpts}}

+}

+\examples{

+  ##

+}

+\keyword{classif}