plot.serp_data: Plot a profile along a gene

In ilia-kats/RiboSeqTools: Tools for analysis of selective ribosome profiling (SeRP) data

Description

For each position, a confidence interval is plotted. Transparency reflects the total number of reads contributing to the confidence interval.

Usage

## S3 method for class 'serp_data'
plot(
  data,
  gene,
  type = c("enrichment", "rpm"),
  samples,
  sample1,
  sample2,
  exp,
  rep,
  bin,
  window_size,
  conf.level = 0.95,
  color = exp,
  highlightregion = list(),
  highlightargs = list()
)

Arguments

data	A serp_data object. Must contain raw (unnormalized) read counts.
gene	Name of the gene/ORF to plot.
type	Plot type. One of enrichment, rpm.
samples	Samples to plot. If missing, all samples will be plotted.
sample1	Name of the first sample (the numerator). If missing, the default sample1 of the data set will be used.
sample2	Name of the second sample (the denominator). If missing, the default sample2 of the data set will be used.
exp	Character vector of experiments to plot. If missing, all experiments are plotted.
rep	Character vector of replicates to plot. If missing, all replicates will be plotted.
bin	Bin level (bynuc or byaa). If missing, the default binning level of the data set will be used.
window_size	Neighborhood size for the confidence interval calculation in nucleotides. If missing, the default window size of the data set will be used.
conf.level	Confidence level.
highlightargs	Named list of additional parameters to pass to annotate. Each list element will be recycled to match the number of annotations.
colaes	Variable to use for the color scale.
higlightregion	Regions in the plot to be highlighted. Can be either a list containing two-element numeric vectors or a two-column matrix. Rectangles spanning the entire height of the plot will be drawn between the given x positions.

Details

If type is enrichment, a binomial confidence interval for enrichment of sample1 compared to sample2 is calculated using binom_ci_profile. The samples argument is ignored.

If type is samples, a Poisson confidence interval for RPM in samples samples is calculated using pois_ci_profile. The upper and lower bounds are then divided by window_size to indicate confidence in the local smoothed read density. The sample1 and sample2 arguments are ignored.

Value

A ggplot object.

See Also

defaults

ilia-kats/RiboSeqTools documentation built on Oct. 5, 2020, 7:41 p.m.