plot_threshold_exploration: Plot Threshold Exploration

In zentnerlab/TSRexploreR: TSS and TSR Analysis

Plot Threshold Exploration

Description

Make a plot to explore threshold values.

Usage

plot_threshold_exploration(
  experiment,
  max_threshold = 25,
  steps = 1,
  samples = "all",
  use_normalized = FALSE,
  ncol = 1,
  point_size = 1,
  return_table = FALSE,
  min_threshold = 1,
  ...
)

Arguments

experiment	TSRexploreR object.
max_threshold	Thresholds from min_count to max_threshold will be explored.
steps	Steps to get the threshold values.
samples	A vector of sample names to analyze.
use_normalized	Whether to use the normalized (TRUE) or raw (FALSE) counts.
ncol	Integer specifying the number of columns to arrange multiple plots.
point_size	The size of the points on the plot.
return_table	Return a table of results instead of a plot.
min_threshold	Thresholds from min_count to max_threshold will be explored.
...	Arguments passed to geom_point.

Details

All TSSs mapping methods produce spurious TSSs. For the most part, these spurious reads TSSs to be weak and somewhat uniformly distributed throughout promoters and gene bodies. This means that this background can be mitigated by requiring a minimum read threshold for a TSS to be considered in downstream analyses.

This plotting function generates a line plot, where the x-axis is the naive read threshold and the y-axis is the proportion of TSSs within annotated gene/transcript promoters. Additionally, the point color represents the absolute number of genes with at least 1 surviving TSS after filtering. 'max_threshold' controls the maximum threshold value explored, and 'steps' is the value that is used to increment between 1 and 'max_threshold'.

At a certain threshold there are diminishing returns, where an increase in threshold results in little increase in promoter-proximal fraction, but a precipitous loss in number of genes with a TSS. A threshold should be chosen that balances these two competing metrics. For STRIPE-seq, we have found that a threshold of 3 often provides an appropriate balance between a high promoter-proximal fraction (>= 0.8) and the number of unique genes or transcripts with at least one unique TSS.

Value

ggplot2 object containing the threshold exploration plot

See Also

apply_threshold to permantly filter TSSs below threshold value.

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_threshold_exploration(exp)

zentnerlab/TSRexploreR documentation built on Dec. 30, 2022, 10:27 p.m.