plot_region_counts: Plots the region counts of UTR5, CDS, and UTR3
In ribor: An R Interface for Ribo Files

Description Usage Arguments Details Value See Also Examples

The function plot_region_counts can take either a DataFrame or a "Ribo" object to generate the a stacked bar plot of proportions that correspond to the "UTR5", "CDS", and "UTR3" regions.

plot_region_counts(
  x,
  experiment,
  range.lower,
  range.upper,
  title = "Region Counts"
)

`x`	A 'Ribo' object or a DataFrame generated from `get_region_counts`
`experiment`	a list of experiment names
`range.lower`	a lower bounds for a read length range
`range.upper`	an upper bounds for a read length range
`title`	a title for the generated plot

When given a 'Ribo' object, plot_region_counts calls get_region_counts to retrieve the necessary information for plotting. This option is in the case that a DataFrame of the region count information is not required.

The user can instead provide a DataFrame with the same structure as the output of the get_region_counts function where the 'transcript' and 'length' parameters are the default values of TRUE. This also means that the remaining parameters of the plot_region_counts function are not necessary. The run time becomes substantially faster when plot_region_counts is given the direct DataFrame to plot. However, the DataFrame needs to follow the format and types in the output of the reading functions

A 'ggplot' of the region counts for each of the experiments

get_region_counts to generate a DataFrame that can be provided as input, Ribo to create a ribo.object that can be provided as input

#ribo object use case
#generate the ribo object
file.path <- system.file("extdata", "sample.ribo", package = "ribor")
sample <- Ribo(file.path)

#specify the regions and experiments of interest
regions <- c("UTR5", "CDS", "UTR3")
experiments <- c("Hela_1", "Hela_2", "WT_1")

plot_region_counts(sample,
                   range.lower = 2,
                   range.upper = 5,
                   experiments)

#DataFrame use case
#obtains the region counts at each individual read length, summed across every transcript
region.counts <- get_region_counts(sample,
                                   region = regions,
                                   range.lower = 2,
                                   range.upper = 5,
                                   tidy = TRUE,
                                   length = TRUE,
                                   transcript = TRUE)

#the params 'length' and 'transcript' must be set to true to use a DataFrame
plot_region_counts(region.counts)