\name{plotCtPairs} \Rdversion{1.1} \alias{plotCtPairs} \title{Pairwise scatterplot of multiple sets of Ct values from qPCR data.} \description{ Produces a plot of high-throughput qPCR Ct values from N number of samples plotted pairwise against each other in an N by N plot. The Ct values will be in the upper triangle, and the correlation between samples in the lower. Features can be marked based on for example feature class or type. } \usage{ plotCtPairs(q, cards = TRUE, lower.panel = panel.Ct.cor, upper.panel = panel.Ct.scatter, Ct.max = 35, col = "type", pch = 20, cex.cor = 2, cex.pch = 1, diag = TRUE, ...) } \arguments{ \item{q}{object of class qPCRset. } \item{cards}{vector, the cards to plot against each other.} \item{lower.panel}{function, to use for plotting the lower triangle.} \item{upper.panel}{function, to use for plotting the upper triangle.} \item{Ct.max}{numeric, Ct values above this limit will be excluded when calculating the correlation.} \item{col}{vector with the colour(s) to use for the points, or a character string ("type" or "class") indicating whether points should be coloured according to \code{featureType} or \code{featureClass} of \code{q}.} \item{pch}{integer or single character, which plotting symbol to use for the points.} \item{cex.cor}{numeric, the expansion factor for the text in \code{panel.Ct.cor}.} \item{cex.pch}{numeric, the expansion factor for the points in \code{panel.Ct.scatter}.} \item{diag}{logical, should the diagonal line y=x be plotted.} \item{\dots}{any other arguments are passed to the panel functon or \code{pairs}.} } %\details{ %% ~~ If necessary, more details than the description above ~~ %} \value{A figure is generated in the current graphics device.} \author{Heidi Dvinge} \seealso{\code{\link{pairs}} or \code{\link{plotCtScatter}} for plotting just two samples. } \examples{ # Load example data data(qPCRraw) # Various types of plot plotCtPairs(qPCRraw, cards=1:4) plotCtPairs(qPCRraw, col="black") plotCtPairs(qPCRraw, Ct.max=40) } % Add one or more standard keywords, see file 'KEYWORDS' in the % R documentation directory. \keyword{hplot }