drawFeatureTrack: Add a 'feature' track to an existing plot

In gmoviz: Seamless visualization of complex genomic variations in GMOs and edited cell lines

Description

Adds to an existing plot a track which displays 'features' (e.g. genes, indels, primer sequences etc) using coloured shapes. Note that you must have initialised the circular plot (by gmovizInitialise first).

Usage

drawFeatureTrack(feature_data, flipped_sector = NULL,
  feature_label_cutoff = 50, track_height = 0.1,
  feature_label_size = 0.9, label_track_height = 0.1 *
  feature_label_size, coverage_rectangle = NULL, coverage_data = NULL,
  internal = FALSE, feature_outline = TRUE)

Arguments

feature_data	A data frame or GRanges containing the 'features' to plot. GRanges input should contain label, colour, shape and track as metadata columns. Data frame should contain label, colour, shape and track, as well as the additional columns chr, start and end Please see below for a detailed description of these columns, and getFeatures for a function which can read this information in from a .gff file.
flipped_sector	A vector of sectors that will have their genomic position (x values) reversed (ascending in anti-clockwise direction, as opposed to the usual ascending in a clock-wise direction).
feature_label_cutoff	To enhance readability when the shapes are small, those labels belonging to features smaller than feature_label_cutoff will instead be plotted on a new track closer to the centre of the circle, rather than inside the shapes themselves.
track_height	The height (proportion of the circle) taken up by each track of features. The default value of 0.1 is appropriate for up to 2 feature tracks; if you get an error due to running out of space please reduce this.
feature_label_size	Size of the feature labels.
label_track_height	Size of the track on which to plot the labels.
coverage_rectangle, coverage_data	If, when initialising the graph you have used coverage_rectangleangle AND you want to plot features on the outermost track (track 0), please fill these in the same as in your gmovizInitialise function call. Otherwise, there is no need to supply these.
internal	For internal use only.
feature_outline	Should a black outline be drawn around the feature shape? (It is recommended to set this to FALSE when dealing with very small features)

Value

Adds a 'feature' track to an existing plot.

Feature data format

The feature data GRanges contains four metadata columns:

label

A character string which will be used to label the feature. It is suggested to keep this label relatively short, if possible.

colour

A character string of a colour to use. Supports hex colours (e.g. #000000) and named R colours (e.g. red).

shape

The shape that will be used to represent the feature:

• 'rectangle'

• 'forward_arrow'

• 'reverse_arrow'

• 'upwards_triangle' (out of the circle).

• 'downwards_triangle' (into the circle).

It is suggested to use 'forward_arrow' for genes on the forward strand and 'reverse_arrow' for genes on the reverse strand.

track

The index of the track on which to plot the feature:

• 0 represents the outermost track, where the ideogram rectangles that represent sequences/chromosomes are plotted.

• 1 is the conventional (default) track on which to plot a feature.

• 2, 3 and so on are further into the centre of the circle.

It is strongly recommended to keep the tracks below 3, otherwise there may not be enough space in the circle to fit them all.

These columns are all optional. If you don't supply them, then default values will be added as follows:

label

''

colour

a colour allocated from rich_colours

shape

'rectangle'

track

1

See Also

featureDiagram for a function that, while slightly less flexible, generates an entire visualisation in one go. Also getFeatures for a function that can read the feature data in from a .gff file.

Examples

## plasmid map
plasmid_ideogram <- data.frame(chr='plasmid', start=0, end=2500)

plasmid_features <- GRanges(seqnames=rep('plasmid', 4),
ranges=IRanges(start=c(0, 451, 901, 1700), end=c(450, 900, 1400, 2200)),
colour = c('#d44a9f', '#4a91d4', '#7ad44a', '#d49d4a'),
label = c('promoter', 'gene', 'GFP', 'ampR'),
shape = c('rectangle', 'forward_arrow', 'forward_arrow', 'reverse_arrow'),
track = rep(1, 4))

## for a simple case like this you might as well use the featureDiagram
## function because it's only 1 function call, whereas here we need two:
gmovizInitialise(plasmid_ideogram)
drawFeatureTrack(plasmid_features)

## however the drawFeatureTrack function allows more flexibility e.g. if you
## want to add features to a plot containing numerical data for example:
## data
scatter_data <- GRanges(rep('plasmid', 50),
IRanges(start=sample(1:3000, 50), width=2),
scatter=rnorm(50, mean=4, sd=1))

## plotting
gmovizInitialise(plasmid_ideogram)
drawScatterplotTrack(plot_data=scatter_data)
drawFeatureTrack(plasmid_features, track_height = 0.15)

gmoviz documentation built on Nov. 8, 2020, 5:41 p.m.