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\name{plot.errorlod}
\alias{plot.errorlod}
\title{Plot grid of error LOD values}
\description{
Plot a grid of the LOD scores indicating which genotypes are
likely to be in error.
}
\usage{
\method{plot}{errorlod}(x, chr, ind, breaks=c(-Inf,2,3,4.5,Inf),
col=c("white","gray85","hotpink","purple3"),
alternate.chrid=FALSE, \dots)
}
\arguments{
\item{x}{An object of class \code{cross}. See
\code{\link[qtl]{read.cross}} for details.}
\item{chr}{The chromosomes for which the error LOD scores should
be plotted.}
\item{ind}{Indicates the individuals for which the error LOD scores
should be plotted.}
\item{breaks}{A set of breakpoints for the colors; must give one more
breakpoint than color. Intervals are open on the left and closed on
the right, except for the lowest interval.}
\item{col}{A vector of colors to appear in the image.}
\item{alternate.chrid}{If TRUE and more than one chromosome is
plotted, alternate the placement of chromosome
axis labels, so that they may be more easily distinguished.}
\item{\dots}{Ignored at this point.}
}
\details{
Uses \code{\link[graphics]{image}} to plot a grid with different shades
of pixels to indicate which genotypes are likely to be in error.
Darker pixels have higher error LOD scores:
\eqn{LOD \le 2} in white;
\eqn{2 < LOD \le 3}{2 < LOD <= 3} in gray;
\eqn{3 < LOD \le 4.5}{3 < LOD <= 4.5} in pink;
\eqn{LOD > 4.5} in purple.
}
\value{None.}
\examples{
data(hyper)
\dontshow{hyper <- subset(hyper,chr=c(1,19))}
# Calculate error LOD scores
hyper <- calc.errorlod(hyper,error.prob=0.01)
# plot the error LOD scores; print those above a specified cutoff
plot.errorlod(hyper)
plot.errorlod(hyper,chr=1)
}
\seealso{ \code{\link[qtl]{calc.errorlod}},
\code{\link[qtl]{top.errorlod}}, \code{\link[graphics]{image}} }
\references{
Lincoln, S. E. and Lander, E. S. (1992) Systematic detection of
errors in genetic linkage data. \emph{Genomics} \bold{14}, 604--610.
}
\author{Karl W Broman, \email{kbroman@biostat.wisc.edu} }
\keyword{hplot}
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