@@ -1,8 +1,8 @@

 Package: crlmm

 Type: Package

 Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for

-        Affymetrix SNP 5.0 and 6.0 and Illumina arrays.

-Version: 1.31.1

+        Affymetrix SNP 5.0 and 6.0 and Illumina arrays

+Version: 1.31.2

 Author: Benilton S Carvalho, Robert Scharpf, Matt Ritchie, Ingo

         Ruczinski, Rafael A Irizarry

 Maintainer: Benilton S Carvalho <benilton@unicamp.br>,

@@ -10,7 +10,7 @@ Maintainer: Benilton S Carvalho <benilton@unicamp.br>,

         <mritchie@wehi.EDU.AU>

 Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0

         arrays, as well as a copy number tool specific to 5.0, 6.0, and

-        Illumina platforms

+        Illumina platforms.

 License: Artistic-2.0

 Depends: R (>= 2.14.0), oligoClasses (>= 1.21.12), preprocessCore (>=

         1.17.7)

new file mode 100644

@@ -0,0 +1,48 @@

+plotSamples = function(cnSet, col=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE, sample=100000, seed=1, type="smoothScatter"){

+    if(missing(col)){

+        stop("col is missing, please specify which sample/(s) to plot")

+    }

+    set.seed(seed)

+    row = sample(nrow(cnSet), sample)

+    if(verbose)  

+      message("compute M values")        

+    M = computeLogRatio(cnSet, offset=offset, verbose=verbose, row=row, col=col)

+    if(type=="beanplot") {

+      sel = rowSums(is.finite(M[,]) & !is.na(M[,]))==ncol(M)

+      beanplot(as.vector(M[sel,])~factor(rep(col, each=sum(sel))), ylab="M", xlab="Sample", ylim=ylim,

+               beanlines="median", what=c(0,1,1,0), col="grey", border="black") #c("#CAB2D6", "#33A02C", "#B2DF8A"), border = "#CAB2D6", 

+      abline(h=0, col="gray", lty=2)

+      delete(M); rm(M)

+    }

+    if(type=="smoothScatter") {

+      if(verbose)

+        message("compute S values")

+      S = computeAverageLogIntensity(cnSet, offset=offset, verbose=verbose, row=row, col=col)

+      for(i in 1:length(col)) {

+        smoothScatter(S[,i], M[,i], main=colnames(M)[i], ylab="M", xlab="S", xlim=xlim, ylim=ylim)

+        abline(h=0, col="gray", lty=2)

+      }

+    delete(S, M); rm(S, M)

+    }

+}

+

+

+plotSNPs = function(cnSet, row=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE){

+    if(missing(row)){

+        stop("row is missing, please specify which SNP/(s) to plot")

+    }

+    if(verbose)  

+      message("compute M values")        

+    M = computeLogRatio(cnSet, offset=offset, verbose=verbose, row=row)

+    if(verbose)

+      message("compute S values")   

+    S = computeAverageLogIntensity(cnSet, offset=offset, verbose=verbose, row=row)

+    if(verbose)

+      message("get genotype calls")

+    for(i in 1:length(row)){

+       plot(S[i,], M[i,], xlab="S", ylab="M", xlim=xlim, ylim=ylim,

+            main=rownames(M)[i], pch=19, col=calls(cnSet)[row[i],])

+       abline(h=0, col="gray", lty=2)

+    }

+    rm(S, M)

+}

new file mode 100644

@@ -0,0 +1,62 @@

+\name{plotSNPs}

+\alias{plotSNPs}

+\alias{plotSamples}

+

+\title{

+	Make M vs S plot for SNPs or samples.

+}

+

+\description{

+	These functions plot the M-values (log-ratios) versus S-values (average intensities)

+        for given SNP/(s) or sample/(s) or beanplots for M-values from different samples.

+}

+

+\usage{

+	plotSNPs(cnSet, row=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE)

+	plotSamples(cnSet, col=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE, sample=100000, seed=1, type="smoothScatter")

+}

+

+\arguments{

+  \item{cnSet}{An object of class \code{CNSet}}

+  \item{row}{scalar/vector of SNP indexes to plot}

+  \item{col}{scalar/vector of sample indexes to plot}

+  \item{offset}{numeric, offset to add to intensities in \code{cnSet} 

+        before log2-transforming to make log-ratios or average log-intensities}

+  \item{xlim}{the x limits of the plot}

+  \item{ylim}{the y limits of the plot}

+  \item{verbose}{'logical.'  Whether to print descriptive messages during processing}

+  \item{sample}{integer indicating the number of SNPs to sample for the plot}

+  \item{seed}{integer seed for the random number generator to sample the SNPs}

+  \item{type}{character vector specifying the type of sample plot (either 'smoothScatter' or 'beanplot')}

+}

+

+\details{

+	The \code{plotSNPs} and \code{plotSamples} functions plot the M and S

+        values derived from the \code{cnSet} object.

+      }

+

+\value{

+      One or more M vs S plot for \code{plotSNPs} for a given SNP(/s)

+      or either a smoothed scatter plot of M vs S or a beanplot of the M-values 

+      for a selected sample(/s) for \code{plotSamples}.

+}

+

+\author{

+      Matt Ritchie and Cynthia Liu

+}

+

+\seealso{

+	\code{\link{genotype.Illumina}}

+}

+\examples{

+\dontrun{

+   crlmmResult <- genotype.Illumina(sampleSheet=samples[1:10,], path=path,

+                                        arrayInfoColNames=list(barcode=NULL,

+                                        position="SentrixPosition"),

+                                        saveDate=TRUE, cdfName="human370v1c")

+   par(mfrow=c(2,2))

+   plotSamples(crlmmResult, col=1:4)

+   plotSNPs(crlmmResult, row=1:4)

+}

+}

+\keyword{hplot}

\ No newline at end of file