plot.varTestBioCond {MAnorm2} | R Documentation |
Plot a varTestBioCond
Object
Description
Given a varTestBioCond
object, which records the results of
calling hypervariable and invariant genomic intervals
across ChIP-seq samples of
a bioCond
object, this method creates a scatter plot of
observed (mean, log10(variance))
pairs
from all genomic intervals, marking
specifically the ones that have a significantly large or small variance.
Besides, the mean-variance curve associated with the bioCond
is also
added to the plot, serving as a baseline to which each observed variance
could be compared.
Usage
## S3 method for class 'varTestBioCond'
plot(
x,
padj = NULL,
pval = NULL,
col = alpha(c("black", "red"), 0.04),
pch = 20,
xlab = "Mean",
ylab = "log10(Var)",
args.legend = list(x = "bottomleft"),
args.lines = list(col = "green3", lwd = 2),
...
)
Arguments
x |
An object of class |
padj , pval |
Cutoff of adjusted/raw p-value for selecting
significant intervals. Only one of the two arguments is effectively
used; |
col , pch |
Optional length-2 vectors specifying the colors and point characters of non-significant and significant intervals, respectively. Elements are recycled if necessary. |
xlab , ylab |
Labels for the X and Y axes. |
args.legend |
Further arguments to be passed to
|
args.lines |
Further arguments to be passed to
|
... |
Further arguments to be passed to
|
Details
Those genomic intervals considered to be significant are actually the ones
that significantly deviate from the mean-variance curve in the plot. See
varTestBioCond
for technical details of the associated
hypothesis testing.
Value
The function returns NULL
.
See Also
bioCond
for creating a bioCond
object from a
set of ChIP-seq samples; fitMeanVarCurve
for fitting a
mean-variance curve; varTestBioCond
for calling
hypervariable and invariant intervals across ChIP-seq samples
contained in a bioCond
object.
Examples
data(H3K27Ac, package = "MAnorm2")
attr(H3K27Ac, "metaInfo")
## Call hypervariable and invariant genomic intervals across biological
## replicates of the GM12891 cell line.
# Perform MA normalization and construct a bioCond to represent GM12891.
norm <- normalize(H3K27Ac, 5:6, 10:11)
GM12891 <- bioCond(norm[5:6], norm[10:11], name = "GM12891")
# Fit a mean-variance curve for GM12891 using the parametric method.
GM12891 <- fitMeanVarCurve(list(GM12891), method = "parametric",
occupy.only = TRUE)[[1]]
summary(GM12891)
plotMeanVarCurve(list(GM12891), subset = "occupied")
# Assess the observed variances of ChIP-seq signal intensities in GM12891.
res <- varTestBioCond(GM12891)
head(res)
# Inspect only the test results of occupied genomic intervals.
res <- res[GM12891$occupancy, ]
res$padj <- p.adjust(res$pval, method = "BH")
plot(res, col = scales::alpha(c("black", "red"), c(0.04, 0.5)))