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Plot brain cell-specific epigenomic data

Source: R/NOTT2019_epigenomic_histograms.R
NOTT2019_epigenomic_histograms.Rd

Brain cell-specific epigenomic data from Nott et al. (2019).

Usage

NOTT2019_epigenomic_histograms(
  dat,
  bigwig_metadata = echoannot::NOTT2019_bigwig_metadata,
  locus_dir = tempdir(),
  show_plot = TRUE,
  save_plot = FALSE,
  full_data = TRUE,
  return_assay_track = FALSE,
  binwidth = 200,
  density_adjust = 0.2,
  zoom = "1x",
  strip.text.y.angle = 90,
  xtext = TRUE,
  geom = "density",
  plot_formula = "Cell_type ~.",
  fill_var = "Assay",
  genomic_units = "Mb",
  as_ggplot = TRUE,
  dpi = 300,
  height = 15,
  width = 8,
  nThread = 1,
  save_annot = FALSE,
  verbose = TRUE
)

Source

Nott et al. (2019) (doi:10.1126/science.aay0793 )

Arguments

dat

Fine-mapping results data from echolocatoR::finemap_loci.

bigwig_metadata

Metadata table with at least the following two columns:

"name"

Unique name of the file.

"data_link"

URL to UCSC genome browser bigwig file.

locus_dir

Locus-specific directory.

show_plot

Show plot.

save_plot

Whether to save the plot.

full_data

Whether to download the full data (genomic ranges of all sequence reads) as opposed to a reduced representation of the data as a single vector (i.e. the aggregated reads "score"). Setting full_data=TRUE is necessary for creating histograms and density plots.

return_assay_track

Return only the assay track (before adding the rest of the tracks and showing the plot).

binwidth

width of the bins.

density_adjust

Passed to adjust argument in geom_density.

zoom

Zoom into the center of the locus when plotting (without editing the fine-mapping results file). You can provide either:

  • The size of your plot window in terms of basepairs (e.g. zoom=50000 for a 50kb window).

  • How much you want to zoom in (e.g. zoom="1x" for the full locus, zoom="2x" for 2x zoom into the center of the locus, etc.).

You can pass a list of window sizes (e.g. c(50000,100000,500000)) to automatically generate multiple views of each locus. This can even be a mix of different style inputs: e.g. c("1x","4.5x",25000).

strip.text.y.angle

Angle of the y-axis facet labels.

xtext

Whether to include x-axis title and text.

geom

defaults for geoms (element_geom())

plot_formula

Formula passed to facets argument in facet_grid.

fill_var

Variable name to use for plot fill argument.

genomic_units

Which genomic units to return window limits in.

as_ggplot

Return plot as ggplot2 (TRUE) or Tracks (FALSE) object.

dpi

dpi to use for raster graphics

height

height (defaults to the height of current plotting window)

width

width (defaults to the width of current plotting window)

nThread

Number of threads to parallelise downloads across.

save_annot

Save the queried subset of bigwig annotations.

verbose

Print messages.

See also

Other NOTT2019: NOTT2019_bigwig_metadata, NOTT2019_get_epigenomic_peaks(), NOTT2019_get_interactions(), NOTT2019_get_interactome(), NOTT2019_get_promoter_celltypes(), NOTT2019_get_promoter_interactome_data(), NOTT2019_get_regulatory_regions(), NOTT2019_plac_seq_plot(), NOTT2019_superenhancers(), get_NOTT2019_interactome(), get_NOTT2019_superenhancer_interactome()

Examples

if (FALSE) { # \dontrun{
nott2019_track <- echoannot::NOTT2019_epigenomic_histograms(
    dat = echodata::BST1, 
    bigwig_metadata = echoannot::NOTT2019_bigwig_metadata[1:2,])
} # }