MAplot.diffBioCond {MAnorm2}

Create an MA Plot on Results of Comparing Two bioCond Objects

Description

This method produces an MA plot demonstrating the results of comparing two bioCond objects. More specifically, it draws a scatter plot consisting of the genomic intervals having been compared, and those intervals with differential ChIP-seq signals between the two conditions are explicitly indicated.

Usage

## S3 method for class 'diffBioCond'
MAplot(
  x,
  padj = NULL,
  pval = NULL,
  col = alpha(c("black", "red"), 0.1),
  pch = 20,
  ylim = c(-6, 6),
  xlab = "A value",
  ylab = "M value",
  args.legend = list(x = "topright"),
  ...
)

Arguments

x

An object of class "diffBioCond", typically obtained by passing two bioCond objects to diffTest.

padj, pval

Cutoff of adjusted/raw p-value for selecting differential intervals. Only one of the two arguments is effectively used; pval is ignored if padj is specified. The default is equivalent to setting padj to 0.1.

col, pch

Optional length-2 vectors specifying the colors and point characters of non-differential and differential intervals, respectively. Elements are recycled if necessary.

ylim

A length-two vector specifying the plotting range of Y-axis (i.e., the M value). Each M value falling outside the range will be shrunk to the corresponding limit. Setting the option to NULL to suppress this behavior.

xlab, ylab

Labels for the X and Y axes.

args.legend

Further arguments to be passed to legend.

...

Further arguments to be passed to plot.

Value

The function returns NULL.

See Also

bioCond for creating a bioCond object; fitMeanVarCurve for fitting a mean-variance curve given a list of bioCond objects; diffTest for making a comparison between two bioCond objects; alpha for adjusting color transparency.

Examples

data(H3K27Ac, package = "MAnorm2")
attr(H3K27Ac, "metaInfo")

## Make a comparison between GM12891 and GM12892 cell lines and create an MA
## plot on the comparison results.

# Perform MA normalization and construct bioConds to represent the two cell
# lines.
norm <- normalize(H3K27Ac, 5:6, 10:11)
norm <- normalize(norm, 7:8, 12:13)
conds <- list(GM12891 = bioCond(norm[5:6], norm[10:11], name = "GM12891"),
              GM12892 = bioCond(norm[7:8], norm[12:13], name = "GM12892"))
autosome <- !(H3K27Ac$chrom %in% c("chrX", "chrY"))
conds <- normBioCond(conds, common.peak.regions = autosome)

# Variations in ChIP-seq signals across biological replicates of a cell line
# are generally of a low level, and their relationship with the mean signal
# intensities is expected to be well modeled by the presumed parametric
# form.
conds <- fitMeanVarCurve(conds, method = "parametric", occupy.only = TRUE)
summary(conds[[1]])
plotMeanVarCurve(conds, subset = "occupied")

# Perform differential tests between the two cell lines.
res <- diffTest(conds[[1]], conds[[2]])
head(res)

# Visualize the overall test results.
MAplot(res, padj = 0.001)
abline(h = 0, lwd = 2, lty = 5, col = "green3")