plot.subsamples

0th

Percentile

plot metrics as a function of subsampled read depth

Plot the number of genes found significant, the Spearman correlation of the effect size estimates with the full experiment, and the empirical false discovery rate as a function of the subsampled read depth. This determines whether these metrics saturate, which indicates that the experiment has an appropriate sequencing depth.

Usage
## S3 method for class 'subsamples':
plot(x, ...)
Arguments
x
a subsamples object
...
further arguments passed to or from other methods.
Details

This is an alias for the plot.summary.subsamples function, so that plotting can be done directly on the subsamples object. We recommend using summary(ss) first, so that the summary operation does not have to be performed each time the figure is plotted, and so the summary object can be examined on its own.

Value

  • plot a subSeq object

Aliases
  • plot.subsamples
Examples
if (interactive()) {
# import the subsampling object (see ?subsample to see how ss is created)
data(ss)

# plot subsample object
plot(ss)
}
Documentation reproduced from package subSeq, version 1.2.2, License: MIT + file LICENSE

Community examples

Looks like there are no examples yet.