genome.plot {RJaCGH} | R Documentation |
Plot of the genome showing, with a color key, the marginal probability of every gene of alteration.
genome.plot(obj, col = NULL, breakpoints = NULL, legend.pos=NULL,...)
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. |
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. |
If col
and breakpoints
are NULL
, a default
color key is drawn.
A plot is drawn.
The positions of the genes should be relative to the chromosome for the plot to make sense.
Oscar M. Rueda and Ramon Diaz Uriarte
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/}.
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))