Nothing
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)
}
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