plot_density: Density Plots

In rpolicastro/tsrexplorer: TSS and TSR Analysis

Description

Generate plots of TSS or TSR positional density relative to annotated TSSs.

Usage

plot_density(
  experiment,
  data_type = c("tss", "tsr"),
  samples = "all",
  consider_score = FALSE,
  upstream = 1000,
  downstream = 1000,
  threshold = NULL,
  ncol = 1,
  use_normalized = FALSE,
  dominant = FALSE,
  exclude_antisense = TRUE,
  data_conditions = NULL,
  color = "default",
  ...
)

Arguments

experiment	TSRexploreR object.
data_type	Whether to plot TSS ('tss') or TSR ('tsr') density.
samples	A vector of sample names to analyze.
consider_score	Whether the score of each TSS or TSR score should be be considered in addition to its unique location.
upstream	Bases upstream of plot center.
downstream	Bases downstream of plot center.
threshold	TSSs or TSRs with a score below this value will not be considered.
ncol	Integer specifying the number of columns to arrange multiple plots.
use_normalized	Whether to use the normalized (TRUE) or raw (FALSE) counts.
dominant	If TRUE, will only consider the highest-scoring TSS per gene, transcript, or TSR or highest-scoring TSR per gene or transcript.
exclude_antisense	Remove antisense TSSs/TSRs prior to analysis.
data_conditions	Apply advanced conditions to the data.
color	Either 'default' or a valid color format to set plot color.
...	Arguments passed to geom_density.

Details

This plotting function generates a density plot of TSS or TSR positions relative to annotated TSSs. The plot is returned as a ggplot2 object.

By default, only the TSS or TSR position is considered, effectively giving every TSS or TSR a score of 1. If 'consider_score' is set to TRUE, the score of each TSS or TSR will be considered when making the plot, giving more weight to stronger TSSs or TSRs.

The region around the annotated TSS used for plotting is controlled by 'upstream' and 'downstream', which should be positive integers.

A set of functions to control data structure for plotting are included. 'use_normalized' will use normalized scores, which only matters if 'consider_score' is TRUE. 'threshold' defines the minimum number of raw counts a TSS or TSR must have to be considered. dominant' specifies whether only the dominant TSS or TSR (determined using the 'mark_dominant' function) is considered. For TSSs, this can be either dominant TSS per TSR or gene/transcript, and for TSRs it is the dominant TSR per gene/transcript. 'data_conditions' can be used to filter, quantile, order, and/or group data for plotting. Finally, 'exclude_antisense' removes anti-sense TSSs or TSRs prior to plotting.

Value

ggplot2 object of density plot.

See Also

annotate_features to annotate TSSs or TSRs.

Examples

data(TSSs_reduced)
annotation <- system.file("extdata", "S288C_Annotation.gtf", package="TSRexploreR")

exp <- TSSs_reduced %>%
  tsr_explorer(genome_annotation=annotation) %>%
  format_counts(data_type="tss") %>%
  annotate_features(data_type="tss")

p <- plot_density(exp, data_type="tss")

rpolicastro/tsrexplorer documentation built on Oct. 17, 2021, 3:02 p.m.