ggDNAvis (version 0.3.2)

visualise_methylation_colour_scale: Visualise methylation colour scalebar

Description

This function creates a scalebar showing the colouring scheme based on methylation probability that is used in visualise_methylation(). Showing this is particularly important when the colour range is clamped via low_clamp and high_clamp (e.g. setting that all values below 100 are fully blue (#0000FF), all values above 200 are fully red (#FF0000), and colour interpolation occurs only in the range 100-200, rather than across the whole range 0-255). If clamping is off (default), then 0 is fully blue, 255 is fully read, and all values are linearly interpolated. NB: colours are configurable but default to blue = low modification probability and red = high modification probability.

Usage

visualise_methylation_colour_scale(
  low_colour = "blue",
  high_colour = "red",
  low_clamp = 0,
  high_clamp = 255,
  full_range = c(0, 255),
  precision = 10^3,
  background_colour = "white",
  x_axis_title = NULL,
  do_x_ticks = TRUE,
  do_side_scale = FALSE,
  side_scale_title = NULL,
  outline_colour = "black",
  outline_linewidth = 1
)

Value

ggplot of the scalebar.

Unlike the other visualise_<> functions in this package, does not directly export a png. This is because there are no squares that need to be rendered at a precise aspect ratio in this function. It can just be saved normally with ggplot2::ggsave() with any sensible combination of height and width.

Arguments

low_colour

character. The colour that should be used to represent minimum probability of methylation/modification (defaults to blue).

high_colour

character. The colour that should be used to represent maximum probability of methylation/modification (defaults to red).

low_clamp

numeric. The minimum probability below which all values are coloured low_colour. Defaults to 0 (i.e. no clamping).

high_clamp

numeric. The maximum probability above which all values are coloured high_colour. Defaults to 255 (i.e. no clamping, assuming Nanopore > SAM style modification calling where probabilities are 8-bit integers from 0 to 255).

full_range

numeric vector, length 2. The total range of possible probabilities. Defaults to c(0, 255), which is appropriate for Nanopore > SAM style modification calling where probabilities are 8-bit integers from 0 to 255.

May need to be set to c(0, 1) if probabilites are instead stored as decimals. Setting any other value is advanced use and should be done for a good reason.

precision

integer. How many different shades should be rendered. Larger values give a smoother gradient. Defaults to 10^3 i.e. 1000, which looks smooth to my eyes and isn't too intensive to calculate.

background_colour

character. The colour the background should be drawn (defaults to white).

x_axis_title

character. The desired x-axis title. Defaults to NULL.

do_x_ticks

logical. Boolean specifying whether x axis ticks should be enabled (TRUE, default) or disabled (FALSE).

do_side_scale

logical. Boolean specifying whether a smaller scalebar should be rendered on the right. Defaults to FALSE.

I think it is unlikely anyone would want to use this, but the option is here. One potential usecase is that this scalebar shows the raw probability values (e.g. 0 to 255), whereas the x-axis is normalised to 0-1.

side_scale_title

character. The desired title for the right-hand scalebar, if turned on. Defaults to NULL.

outline_colour

character. The colour of the scalebar outline. Defaults to black.

outline_linewidth

numeric. The linewidth of the scalebar outline. Defaults to 1. Set to 0 to disable scalebar outline.

Examples

## Defaults match defaults of visualise_methylation()
visualise_methylation_colour_scale()

## Use clamping and change colours
visualise_methylation_colour_scale(
    low_colour = "white",
    high_colour = "black",
    low_clamp = 0.3*255,
    high_clamp = 0.7*255,
    full_range = c(0, 255),
    background_colour = "lightblue1",
    x_axis_title = "Methylation probability"
)

## Lower precision = colour banding
visualise_methylation_colour_scale(
    precision = 10,
    do_x_ticks = FALSE
)