xyplot: Plot prediction regions and normalized intensities.
| xyplot | R Documentation |
Plot prediction regions and normalized intensities.
Description
Plot prediction regions for integer copy number and normalized intensities.
Usage
xyplot(x, data, ...)
Arguments
x |
A |
data |
A |
... |
Additional arguments passed to |
Value
A trellis object.
Author(s)
R. Scharpf
See Also
xyplot, ABpanel
Examples
library(oligoClasses)
data(cnSetExample2)
table(batch(cnSetExample2))
sample.index <- which(batch(cnSetExample2) == "CUPID")
## A single SNP
pr <- predictionRegion(cnSetExample2[1:4, sample.index], copyNumber=0:4)
gt <- calls(cnSetExample2[1:4, sample.index])
lim <- c(6,13)
xyplot(B~A|snpid, data=cnSetExample2[1:4, sample.index],
predictRegion=pr,
panel=ABpanel,
pch=21,
fill=c("red", "blue", "green3")[gt],
xlim=lim, ylim=lim)
## multiple SNPs, prediction regions for 3 batches
## Not run:
tab <- table(batch(cnSetExample2))
bns <- names(tab)[tab > 50]
sample.index <- which(batch(cnSetExample2)
pr <- predictionRegion(cnSetExample2[1:10, sample.index], copyNumber=0:4)
gt <- as.integer(calls(cnSetExample2[1:10, sample.index]))
xyplot(B~A|snpid, data=cnSetExample2[1:10, sample.index],
predictRegion=pr,
panel=ABpanel,
pch=21,
fill=c("red", "blue", "green3")[gt],
xlim=c(6,12), ylim=c(6,12))
## nonpolymorphic markers
data(cnSetExample2)
tab <- table(batch(cnSetExample2))
bns <- names(tab)[tab > 50]
sample.index <- which(batch(cnSetExample2)
np.index <- which(!isSnp(cnSetExample2))[1:10]
taus <- tau2(cnSetExample)[np.index, , , ]
pr <- predictionRegion(cnSetExample2[np.index, sample.index],
copyNumber=0:4)
pp <- posteriorProbability(cnSetExample2[np.index, sample.index],
predictRegion=pr,
copyNumber=0:4)
## End(Not run)
