plotPatterns: plotPatterns
In BBCG/epialleleR: Fast, Epiallele-Aware Methylation Caller and Reporter

plotPatterns

R Documentation

plotPatterns

Description

This convenience function plots methylation patterns (epialleles) previously extracted by extractPatterns.

Usage

plotPatterns(
  patterns,
  order.by = c("beta", "count"),
  beta.range = c(0, 1),
  bin.context = c("CG", "CHG", "CHH", "CxG", "CX"),
  nbins = 10,
  npatterns.per.bin = 2,
  plot.context = c("CG", "CHG", "CHH", "CxG", "CX"),
  genomic.scale = c("continuous", "discrete"),
  breaks = "auto",
  marginal = c("density", "count"),
  marginal.position = c("left", "right"),
  marginal.transform = c("identity", "log10"),
  marginal.limits = NULL,
  marginal.size = 0.25,
  ...,
  tag = c("none", "count", "beta", "pattern"),
  tag.size = 2.5,
  tag.colour = "#87654c",
  tag.fill = "lemonchiffon",
  title = TRUE,
  subtitle = TRUE,
  context.size = c(1, 2, 3),
  base.size = 3,
  methylation.fill = c("grey97", "grey10"),
  plot = TRUE,
  verbose = TRUE
)

Arguments

`patterns`	output of `preprocessBam` function (methylation patterns as a `data.table` object).
`order.by`	string defining order of patterns on the plot (default order by: "beta").
`beta.range`	numeric vector of length 2 for the range of average pattern beta values represented on the plot (default: [0;1]).
`bin.context`	string defining cytosine methylation context used to calculate average beta value of a pattern that is further used to assign patterns to bins: "CG" (the default) – CpG cytosines (called as zZ) "CHG" – CHG cytosines (xX) "CHH" – CHH cytosines (hH) "CxG" – CG and CHG cytosines (zZxX) "CX" – all cytosines
`nbins`	a single integer defining the number of bins (i.e., intervals within 'beta.range'). Default: 10.
`npatterns.per.bin`	integer vector for the number of the most abundant patterns selected from each bin (default: 2). When of length 1, the same number of patterns will be taken. When of length 'nbins', allows to fine-tune the number of selected patterns from each bin. Setting to 'Inf' effectively results in plotting all patterns.
`plot.context`	string defining methylation context of cytosines included in the plot (default: "CG"; for the range of available values, see 'bin.context' above).
`genomic.scale`	string for the type of genomic position scale of the plot: either "continuous" (the default) or "discrete".
`breaks`	a vector of breaks for the genomic position scale of the plot. If "auto" (the default), breaks for continuous scale are computed by the default ggplot2 routines, while breaks for discrete scale are a subset of plotted positions selected using `pretty`. Possible values: `ggplot2::waiver()` for ggplot2 defaults, integer vector of breaks for continuous scale, or character vector of breaks for discrete scale.
`marginal`	string for the type of marginal plot: either "density" (probability density of average beta values of all patterns; the default) or "count" (counts of plotted patterns). "none" is not implemented yet; create an issue if interested.
`marginal.position`	string for the position of marginal plot: either "left" (the default) or "right" (not implemented yet; create an issue if interested).
`marginal.transform`	string for the transformation of marginal scale (default: "identity"). Check `ggplot2::scale_x_continuous()` for more details.
`marginal.limits`	limits of marginal scale (default: NULL). Check `ggplot2::scale_x_continuous()` for more details.
`marginal.size`	numeric in range (0;1) for the relative width of the marginal plot (default: 0.25).
`...`	additional arguments passed to `stats::density()` call used in marginal density plot. Possible value: `adjust=0.25`.
`tag`	string for optional tagging of patterns with their count ("count"), average beta value ("beta"), or pattern ID ("pattern"). Default: "none".
`tag.size`	numeric for the font size of the tag text (in millimetres; default: 2.5).
`tag.colour`	string for the colour of of the tag text. Default: "#87654c".
`tag.fill`	string for the colour of of the tag background. Default: "lemonchiffon".
`title`	the title of the plot. When 'TRUE' (the default), a genomic region from which patterns were extracted. Other possible values: anything that can be converted to string, or 'NULL' for no title.
`subtitle`	the subtitle of the plot. When 'TRUE' (the default), a number of patterns plotted. Other possible values: anything that can be converted to string, or 'NULL' for no subtitle.
`context.size`	a numeric vector with sizes of circles representing cytosines within each of three contexts: CHH, CHG, and CG (default: c(1, 2, 3)).
`base.size`	numeric for the font size of the text for highlighted bases (in millimetres; default: 3).
`methylation.fill`	a vector of length 2 for colours representing unmethylated and methylated cytosines, respectively. These colours are also mapped to the lowest (0) and highest (1) possible beta values to represent average beta values of methylation patterns and create a gradient fill of a marginal density plot. Default: c("grey97", "grey10").
`plot`	boolean. If 'TRUE' (the default), patterns are plotted, and the selected ones are silently returned as a `data.table` object. If 'FALSE', the `grob table` object is returned instead.
`verbose`	boolean to report basic info on input and output.

Details

As the number of methylation patterns can be quite large, by default, the function plots the most abundant unique patterns only. The complete logic is as follows:

from the input methylation patterns, all unique patterns are extracted and counted
unique patterns are split in bins by their average beta value
most abundant unique methylation patterns from each bin are plotted and silently returned

On the resulting plot, each cytosine is shown as a circle, where the size of that circle represents cytosine context and the fill encodes methylation status. If available, highlighted bases are shown as labels of different colours.

Value

the plot and (silently) the data.table object containing plotted methylation patterns (if 'plot==TRUE'), or grob table object (if 'plot==FALSE').

Examples

  # amplicon data
  amplicon.bam <- system.file("extdata", "amplicon010meth.bam",
                              package="epialleleR")
  custom.range <- as("chr17:43124861-43125150", "GRanges")
  
  # let's get our patterns
  patterns <- extractPatterns(bam=amplicon.bam, bed=custom.range)
  
  # default plot + silently returned plotted patterns
  selected.patterns <- plotPatterns(patterns)
  
  # all unique patterns with their counts as a margin, categorical positions,
  # tagged with pattern IDs, returned as a `gtable` object
  tbl <- plotPatterns(patterns, npatterns.per.bin=Inf, marginal="count",
                      genomic.scale="discrete", tag="pattern", plot=FALSE)
  
  # which can be plotted later
  grid::grid.newpage()
  grid::grid.draw(tbl)

BBCG/epialleleR documentation built on Nov. 19, 2024, 3:59 p.m.