RJaCGH (version 1.1.1)

genome.plot: 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, legend.pos=NULL,...)

Arguments

obj

An object of class RJaCGH.Chrom, RJaCGH.genome or RJaCGH.array.

col

A vector of length k for the color of every range of probabilities of alteration, starting from loss to gain.

breakpoints

A vector of length k-1 for the breakpoints of the color key. The corresponding to losses must be negative. See example for details.

legend.pos

Position of the legend. Must be a vector with two elements; the position of the x and y coordinates. If NULL, the legend is placed at the right.

...

Aditional parameters passed to plot.

Value

• A plot is drawn.

Details

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

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))