plotCoverage: Plot read coverage across genomic regions

Description Usage Arguments Value Examples

View source: R/wiggleplotr.R

Description

Also supports rescaling introns to constant length. Does not work on Windows, because rtracklayer cannot read BigWig files on Windows.

Usage

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plotCoverage(exons, cdss = NULL, transcript_annotations = NULL,
  track_data, rescale_introns = TRUE, new_intron_length = 50,
  flanking_length = c(50, 50), plot_fraction = 0.1, heights = c(0.75,
  0.25), alpha = 1, fill_palette = c("#a1dab4", "#41b6c4", "#225ea8"),
  mean_only = TRUE, connect_exons = TRUE, transcript_label = TRUE,
  return_subplots_list = FALSE, region_coords = NULL,
  coverage_type = "area")

Arguments

exons

list of GRanges objects, each object containing exons for one transcript. The list must have names that correspond to transcript_id column in transript_annotations data.frame.

cdss

list of GRanges objects, each object containing the coding regions (CDS) of a single transcript. The list must have names that correspond to transcript_id column in transript_annotations data.frame. If cdss is not specified then exons list will be used for both arguments. (default: NULL).

transcript_annotations

Data frame with at least three columns: transcript_id, gene_name, strand. Used to construct transcript labels. (default: NULL)

track_data

data.frame with the metadata for the bigWig read coverage files. Must contain the following columns:

  • sample_id - unique id for each sample.

  • track_id - if multiple samples (bigWig files) have the same track_id they will be overlayed on the same plot, track_id is also used as the facet label on the right.

  • bigWig - path to the bigWig file.

  • scaling_factor - normalisation factor for each sample, useful if different samples sequenced to different depth and bigWig files not normalised for that.

  • colour_group - additional column to group samples into, is used as the colour of the coverage track.

rescale_introns

Specifies if the introns should be scaled to fixed length or not. (default: TRUE)

new_intron_length

length (bp) of introns after scaling. (default: 50)

flanking_length

Lengths of the flanking regions upstream and downstream of the gene. (default: c(50,50))

plot_fraction

Size of the random sub-sample of points used to plot coverage (between 0 and 1). Smaller values make plotting significantly faster. (default: 0.1)

heights

Specifies the proportion of the height that is dedicated to coverage plots (first value) relative to transcript annotations (second value). (default: c(0.75,0.25))

alpha

Transparency (alpha) value for the read coverage tracks. Useful to set to something < 1 when overlaying multiple tracks (see track_id). (default: 1)

fill_palette

Vector of fill colours used for the coverage tracks. Length must be equal to the number of unique values in track_data$colour_group column.

mean_only

Plot only mean coverage within each combination of track_id and colour_group values. Useful for example for plotting mean coverage stratified by genotype (which is specified in the colour_group column) (default: TRUE).

connect_exons

Print lines that connect exons together. Set to FALSE when plotting peaks (default: TRUE).

transcript_label

If TRUE then transcript labels are printed above each transcript. (default: TRUE).

return_subplots_list

Instead of a joint plot return a list of subplots that can be joined together manually.

region_coords

Start and end coordinates of the region to plot, overrides flanking_length parameter.

coverage_type

Specifies if the read coverage is represented by either 'line', 'area' or 'both'. The 'both' option tends to give better results for wide regions. (default: area).

Value

Either object from cow_plot::plot_grid() function or a list of subplots (if return_subplots_list == TRUE)

Examples

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require("dplyr")
require("GenomicRanges")
sample_data = dplyr::data_frame(sample_id = c("aipt_A", "aipt_C", "bima_A", "bima_C"), 
    condition = factor(c("Naive", "LPS", "Naive", "LPS"), levels = c("Naive", "LPS")), 
    scaling_factor = 1) %>%
    dplyr::mutate(bigWig = system.file("extdata",  paste0(sample_id, ".str2.bw"), package = "wiggleplotr"))

track_data = dplyr::mutate(sample_data, track_id = condition, colour_group = condition)

selected_transcripts = c("ENST00000438495", "ENST00000392477") #Plot only two transcripts of the gens
## Not run: 
plotCoverage(ncoa7_exons[selected_transcripts], ncoa7_cdss[selected_transcripts], 
   ncoa7_metadata, track_data, 
   heights = c(2,1), fill_palette = getGenotypePalette())

## End(Not run)

kauralasoo/wiggleplotr documentation built on July 21, 2021, 4:15 a.m.