plot_region: Plot region methylation

In Shians/NanoMethViz: Visualise methylation data from Oxford Nanopore sequencing

Plot region methylation

Description

Plot the methylation of a genomic region.

Usage

plot_region(x, chr, start, end, ...)

## S4 method for signature 'NanoMethResult,character,numeric,numeric'
plot_region(
  x,
  chr,
  start,
  end,
  anno_regions = NULL,
  binary_threshold = NULL,
  avg_method = c("mean", "median"),
  spaghetti = FALSE,
  heatmap = TRUE,
  heatmap_subsample = 50,
  smoothing_window = 2000,
  gene_anno = TRUE,
  window_prop = 0,
  palette = ggplot2::scale_colour_brewer(palette = "Set1"),
  line_size = 1,
  mod_scale = c(0, 1),
  span = NULL
)

## S4 method for signature 'ModBamResult,character,numeric,numeric'
plot_region(
  x,
  chr,
  start,
  end,
  anno_regions = NULL,
  binary_threshold = NULL,
  avg_method = c("mean", "median"),
  spaghetti = FALSE,
  heatmap = TRUE,
  heatmap_subsample = 50,
  smoothing_window = 2000,
  gene_anno = TRUE,
  window_prop = 0,
  palette = ggplot2::scale_colour_brewer(palette = "Set1"),
  line_size = 1,
  mod_scale = c(0, 1),
  span = NULL
)

## S4 method for signature 'NanoMethResult,factor,numeric,numeric'
plot_region(
  x,
  chr,
  start,
  end,
  anno_regions = NULL,
  binary_threshold = NULL,
  avg_method = c("mean", "median"),
  spaghetti = FALSE,
  heatmap = TRUE,
  heatmap_subsample = 50,
  smoothing_window = 2000,
  gene_anno = TRUE,
  window_prop = 0,
  palette = ggplot2::scale_colour_brewer(palette = "Set1"),
  line_size = 1,
  mod_scale = c(0, 1),
  span = NULL
)

## S4 method for signature 'ModBamResult,factor,numeric,numeric'
plot_region(
  x,
  chr,
  start,
  end,
  anno_regions = NULL,
  binary_threshold = NULL,
  avg_method = c("mean", "median"),
  spaghetti = FALSE,
  heatmap = TRUE,
  heatmap_subsample = 50,
  smoothing_window = 2000,
  gene_anno = TRUE,
  window_prop = 0,
  palette = ggplot2::scale_colour_brewer(palette = "Set1"),
  line_size = 1,
  mod_scale = c(0, 1),
  span = NULL
)

Arguments

x	the NanoMethResult or ModBamResult object.
chr	the chromosome to plot.
start	the start of the plotting region.
end	the end of the plotting region.
...	additional arguments.
anno_regions	the data.frame of regions to be annotated.
binary_threshold	the modification probability such that calls with modification probability above the threshold are set to 1 and probabilities equal to or below the threshold are set to 0.
avg_method	the average method for pre-smoothing at each genomic position. Data is pre-smoothed at each genomic position before the smoothed aggregate line is generated for performance reasons. The default is "mean" which corresponds to the average methylation fraction. The alternative "median" option is closer to an average within the more common methylation state.
spaghetti	whether or not individual reads should be shown.
heatmap	whether or not read-methylation heatmap should be shown.
heatmap_subsample	how many packed rows of reads to subsample to.
smoothing_window	the window size for smoothing the trend line.
gene_anno	whether to show gene annotation.
window_prop	the size of flanking region to plot. Can be a vector of two values for left and right window size. Values indicate proportion of gene length.
palette	the ggplot colour palette used for groups.
line_size	the size of the lines.
mod_scale	the scale range for modification probabilities. Default c(0, 1), set to "auto" for automatic limits.
span	DEPRECATED, use smoothing_window instead. Will be removed in next version.

Details

This function plots the methylation data for a given region. The main trendline plot shows the average methylation probability across the region. The heatmap plot shows the methylation probability for each read across the region. The gene annotation plot shows the exons of the region. In the heatmap, each row represents one or more non-overlapping reads where the coloured segments represent the methylation probability at each position. Data along a read is connected by a grey line. The gene annotation plot shows the isoforms and exons of genes within the region, with arrows indicating the direction of transcription.

Since V3.0.0 NanoMethViz has changed the smoothing strategy from a loess smoothing to a weighted moving average. This is because the loess smoothing was too computationally expensive for large datasets and had a span parameter that was difficult to tune. The new smoothing strategy is controlled by the smoothing_window argument.

Value

a patchwork plot containing the methylation profile in the specified region.

Examples

nmr <- load_example_nanomethresult()
plot_region(nmr, "chr7", 6703892, 6730431)

Shians/NanoMethViz documentation built on Jan. 17, 2025, 11:19 p.m.