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Plotting read classes data per category assigned to the analyzed reads.

Source: R/ninetails_plotting_functions.R
plot_class_counts.Rd

This function requires as input the dataframe with read_classes provided by ninetails pipeline. Function works in 3 flavours, by plotting either:

  • detailed classification (based on column "comments")

  • crude classification (based on column "class")

  • reads decorated with non-As exclusively

Usage

plot_class_counts(
  class_data,
  grouping_factor = NA,
  frequency = TRUE,
  type = "R"
)

Arguments

class_data

A dataframe or tibble containing read_classes predictions made by ninetails pipeline

grouping_factor

character string. A grouping variable (e.g. "sample_name")

frequency

logical [TRUE/FALSE]. If TRUE, the frequency will be plotted. If FALSE, raw counts will be shown. This parameter is set to TRUE by default.

type

character string ["R"/"N"/"A"]. This variable controls the level of detail of the resulting plot:

  • "R" - detailed classification (based on column "comments")

  • "N" - crude classification (based on column "class")

  • "A" - reads decorated with non-As exclusively

By default, the "R" option is set.

Value

ggplot object with read class prediction

Details

Function based on the Nanotail equivalent: https://github.com/LRB-IIMCB/nanotail Many thanks to smeagol (Pawel Krawczyk) for advice & support!

Examples

if (FALSE) { # \dontrun{

ninetails::plot_class_counts(class_data=read_classes_dataframe,
                             grouping_factor="sample_name",
                             frequency=TRUE,
                             type="R")
} # }