plotAMR: Plot aberrantly methylated regions

plotAMRR Documentation

Plot aberrantly methylated regions

Description

'plotAMR' uses 'ggplot2' to visualize aberrantly methylated regions (AMRs) at particular genomic locations.

Usage

plotAMR(
  data.ranges,
  data.samples = NULL,
  amr.ranges,
  highlight = NULL,
  title = NULL,
  labs = c("genomic position", "beta value"),
  window = 300
)

Arguments

data.ranges

A 'GRanges' object with genomic locations and corresponding beta values included as metadata.

data.samples

A character vector with sample names (a subset of metadata column names) to be included in the plot. If 'NULL' (the default), then all samples (metadata columns) are included.

amr.ranges

An output of 'getAMR' - a 'GRanges' object that contain aberrantly methylated regions (AMRs).

highlight

An optional list of samples to highlight. If NULL (the default), will contain sample IDs from the 'sample' metadata column of 'amr.ranges' object.

title

An optional title for the plot. If NULL (the default), plot title is set to a genomic location of particular AMR.

labs

Optional axis labels for the plot. Default: c("genomic position", "beta value").

window

An optional integer constant to expand genomic ranges of the 'amr.ranges' object (the default: 300).

Details

For every non-overlapping genomic location from 'amr.ranges' object, 'plotAMR' plots and outputs a line graph of methylation beta values taken from 'data.ranges' for all samples from 'data.samples'. Samples bearing significantly different methylation profiles ('sample' column of 'amr.ranges' object) are highlighted.

Value

The output is a list of 'ggplot' objects.

See Also

getAMR for identification of AMRs, getUniverse for info on enrichment analysis, simulateAMR and simulateData for the generation of simulated test data sets, and 'ramr' vignettes for the description of usage and sample data.

Examples

  data(ramr)
  plotAMR(ramr.data, ramr.samples, ramr.tp.unique[1])
  library(gridExtra)
  do.call("grid.arrange",
          c(plotAMR(ramr.data, ramr.samples, ramr.tp.nonunique), ncol=2))

BBCG/ramr documentation built on Dec. 17, 2024, 3:49 p.m.