genome.plot {RJaCGH}R Documentation

Plot of the genome with probabilities of alteration.

Description

Plot of the genome showing, with a color key, the marginal probability of every gene of alteration.

Usage

genome.plot(obj, col = NULL, breakpoints = NULL)

Arguments

obj An object of class RJaCGH.Chrom, RJaCGH.genome or RJaCGH.array.
col A vector of length texttt{k} for the color of every range of probabilities of alteration, starting from loss to gain.
breakpoints A vector of length texttt{k-1} for the breakpoints of the color key. The corresponding to losses must be negative. See example for details.

Details

If col and breakpoints are NULL, a default color key is drawn.

Value

A plot is drawn.

Note

The positions of the genes should be relative to the chromosome for the plot to make sense.

Author(s)

Oscar M. Rueda and Ramon Diaz Uriarte

References

Oscar M. Rueda and Ramon Diaz Uriarte. A flexible, accurate and extensible statistical method for detecting genomic copy-number changes. http://biostats.bepress.com/cobra/ps/art9/. {http://biostats.bepress.com/cobra/ps/art9/}.

Examples

data(snijders)
y <- gm13330$LogRatio[!is.na(gm13330$LogRatio)]
Pos <- gm13330$PosBase[!is.na(gm13330$LogRatio)]
Chrom <- gm13330$Chromosome[!is.na(gm13330$LogRatio)]

jp <- list(sigma.tau.mu=rep(0.05, 4), sigma.tau.sigma.2=rep(0.03, 4),
           sigma.tau.beta=rep(0.07, 4), tau.split.mu=0.1, tau.split.beta=0.1)
fit.genome <- RJaCGH(y=y, Pos=Pos, Chrom=Chrom, model="genome",
burnin=1000, TOT=1000, jump.parameters=jp, k.max = 4)
genome.plot(fit.genome)
genome.plot(fit.genome, col=c(3, 1, 2), breakpoints=c(-0.5, 0.5))

[Package RJaCGH version 1.0.2 Index]