RJaCGH (version 2.0.3)

genomePlot: 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

genomePlot(obj, array=NULL, weights=NULL, 
col = NULL, breakpoints = NULL, legend.pos=NULL,...)

Arguments

obj

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

array

Name of the array to be plotted. If NULL, the weigthed average of all is computed.

weights

vector of weights for each array. Must have the length of the number of arrays. If NULL, the weights are uniform.

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

Rueda OM, Diaz-Uriarte R. Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH. PLoS Comput Biol. 2007;3(6):e122

Examples

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

## Sort positions

for (i in unique(Chrom)) {
if(any(diff(Pos[Chrom==i]) < 0)) {
id <- order(Pos[Chrom==i])
y[Chrom==i] <- y[Chrom==i][id]
Pos[Chrom==i] <- Pos[Chrom==i][id]
}
}

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)
genomePlot(fit.genome)
genomePlot(fit.genome, col=c(3, 1, 2), breakpoints=c(-0.5, 0.5))