featureDiagram: Display 'features' of interest in a diagram

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

Description

Generates a diagram which displays 'features' (e.g. genes, indels, primer sequences etc) using coloured shapes. See insertionDiagram for a similar function which specialises in plotting insertions or drawFeatureTrack to add a feature track to an existing graph.

Usage

featureDiagram(ideogram_data, feature_data, start_degree = 180,
  coverage_rectangle = NULL, coverage_data = NULL,
  custom_sector_width = NULL, space_between_sectors = 4,
  flipped_sector = NULL, sector_colours = nice_colours,
  sector_border_colours = nice_colours, sector_labels = TRUE,
  sector_label_size = 1.3, sector_label_colour = "black",
  label_data = NULL, label_size = 1.1, label_colour = "black",
  xaxis = TRUE, xaxis_label_size = 0.9, xaxis_colour = "#747577",
  xaxis_spacing = 10, feature_label_cutoff = 50,
  xaxis_spacing_unit = "deg", track_height = 0.1,
  feature_label_size = 0.9, link_data = NULL,
  link_colour = "#84c6d6", link_ends = "default", custom_ylim = NULL,
  label_track_height = 0.1 * feature_label_size,
  feature_outline = TRUE)

Arguments

ideogram_data	Either a GRanges representing regions of interest or a data frame in bed format (containing the chr, start and end columns). If you want to read in data from file, please see the getIdeogramData function.
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.
start_degree	Where on the circle the first sector will start being drawn from (90 = 12 o'clock).
coverage_rectangle	A vector containing the name(s) of any sector(s) that you would like to depict as 'coverage rectangles': filled in shapes that are a plot of the coverage data over that sector. See the example below or the vignette for an example of this.
coverage_data	A GRanges (or data frame) containing the coverage data to plot for those sectors in coverage_rectangle. To read this data in from a BAM file, please see the getCoverage function.
custom_sector_width	Normally, the size of each sector is proportional to its relative length, but custom_sector_width can change this. It is a vector of sector sizes (as proportions of the entire circle), given in the same order in which sectors are plotted: firstly 'chr1', 'chr2' ... through to 'chrX' and 'chrY' followed by any differently named sectors e.g. 'gene 1', plasmid' in alphabetical order.
space_between_sectors	Space between each sector.
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).
sector_colours	Either a single colour (which will be applied to all sectors) or a vector with the same length as the number of sectors/regions. This package includes 5 colour sets: nice_colours, pastel_colours, bright_colours_transparent, bright_colours_opaque and rich_colours. See colourSets for more information about these.
sector_border_colours	Same as sector_colours, only for the border of each sector.
sector_labels	If TRUE, labels ('chr1', 'chr2' etc.) will be drawn for each sector (recommended).
sector_label_size	Size of the sector labels.
sector_label_colour	Colour of the sector labels.
label_data	Data frame or GRanges containing the labels. If a GRanges, label should be a metadata column containing the character strings of the labels. type and colour can also be used to store additional information about the type (e.g. 'gene' or 'promoter') and colour of the label. This information can be used to colour code the labels by supplying the colour column as the label_colour parameter. Data frames should additionally include the chr, start, end which dictate the position of the label.
label_size	Size of the labels.
label_colour	Colour of the labels, can be either a single value (applied to all labels) or a vector with the same length as the number of labels (for colour-coding).
xaxis	If TRUE, an x (genomic position) xaxis will be plotted.
xaxis_label_size	Size of the x axis labels.
xaxis_colour	Colour of the x axis labels.
xaxis_spacing	Space between the x axis labels, in degrees. Alternatively, the string 'start_end' will place a label at the start and end of each sector only.
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.
xaxis_spacing_unit	Either "deg" to draw ticks every certain number of degrees around the circle or "bp" to draw ticks every certain bp around the circle (be warned that when the scales for each sector are very different, it's best to use "deg")
track_height	The height (vertical distance around the circle) that will be taken up by this track. Should be a number between 0 (none) and 1 (entire circle).
feature_label_size	Size of the feature labels.
link_data	If you would like to draw a link between two sectors of the circle, link_data should be a data frame with two rows: one for each end of the link. There should be 3 columns: chr, start & end which describe the position of each end of the link.
link_colour	The colour of the link: this should be a 6 digit hex code, the transparency is automatically added.
link_ends	How far the link extends in either direction. This is set automatically but if you want to edit it, provide a vector of length 2 with each element being between 0 (centre of circle) and 1 (right at the edge of the circle).
custom_ylim	A vector of length two containing the y (coverage) axis limits. No need to set if not using coverage rectangles or if you're happy with the default: c(0, maximum coverage).
label_track_height	Size of the track on which to plot the labels.
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

Generates an image of the feature data supplied.

Warning

If you choose to use a data frame to supply the feature data, please be careful to add the stringsAsFactors = FALSE argument. Otherwise, the colours may not be correct.

See Also

insertionDiagram for a more specialised function which shows the copy number of insertions. Also drawFeatureTrack to add the exact same feature information to an existing plot and getFeatures for a function that can read in the feature information 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))

featureDiagram(plasmid_ideogram, plasmid_features)

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