Plot brain cell-specific interactome data

Plot brain cell-specific interactome data from Nott et al. (2019).

NOTT2019_plac_seq_plot(
  dat = NULL,
  locus_dir = NULL,
  title = NULL,
  show_plot = TRUE,
  save_plot = TRUE,
  return_interaction_track = FALSE,
  x_limits = NULL,
  zoom_window = NULL,
  index_SNP = NULL,
  genomic_units = "POS",
  color_dict = c(enhancers = "springgreen2", promoters = "purple", anchors = "black"),
  highlight_plac = TRUE,
  show_regulatory_rects = TRUE,
  show_anchors = TRUE,
  strip.text.y.angle = 0,
  xtext = TRUE,
  save_annot = FALSE,
  point_size = 2,
  height = 7,
  width = 7,
  dpi = 300,
  return_as = "Tracks",
  nThread = 1,
  verbose = TRUE
)

Source

Nott et al. (2019)

Arguments

dat

Fine-mapping results data from finemap_loci.

locus_dir

Locus-specific directory.

title

all title elements: plot, axes, legends (element_text(); inherits from text)

show_plot

Print plot.

save_plot

Whether to save the plot.

return_interaction_track

Return only the interaction track (before completing the plot and showing it).

x_limits

x-axis limits to be applied to all plots (useful when trying to keep a common coordinate system).

zoom_window

Zoom window.

index_SNP

Index/lead SNP RSID.

genomic_units

Which genomic units to return window limits in.

color_dict

Named list of colors for each regulatory element.

highlight_plac

Whether to scale opacity of PLAC-seq interactions (arches) such that interactions with anchors containing Consensus SNPs will be colored darker (Default: TRUE). If FALSE, will instead apply the same opacity level to all interactions.

show_regulatory_rects

Show enhancers/promoters as rectangles.

show_anchors

Show PLAC-seq anchors.

strip.text.y.angle

Angle of the y-axis facet labels.

xtext

Whether to include x-axis title and text.

save_annot

Save the queried subset of bigwig annotations.

point_size

Point size of each SNP in the GWAS/fine-mapping plots.

height

height (defaults to the height of current plotting window)

width

width (defaults to the width of current plotting window)

dpi

dpi to use for raster graphics

return_as

Plot class to convert plot_list to:

• "ggplot"ggplot

• "ggbio"ggbio

• "patchwork"patchwork

• "Tracks"tracks

• NULLReturn original object.

nThread

Number of threads to parallelise downloads across.

verbose

Print messages.

See also

Other NOTT2019: NOTT2019_bigwig_metadata, NOTT2019_epigenomic_histograms(), NOTT2019_get_epigenomic_peaks(), NOTT2019_get_interactions(), NOTT2019_get_interactome(), NOTT2019_get_promoter_celltypes(), NOTT2019_get_promoter_interactome_data(), NOTT2019_get_regulatory_regions(), NOTT2019_superenhancers(), get_NOTT2019_interactome(), get_NOTT2019_superenhancer_interactome()

Examples

trks_plus_lines <- echoannot::NOTT2019_plac_seq_plot(dat = echodata::BST1) 
#> NOTT2019:: Creating PLAC-seq interactome plot
#> ++ NOTT2019:: Getting promoter cell-type-specific data.
#> ++ NOTT2019:: Getting interactome data.
#> ++ NOTT2019:: Getting regulatory regions data.
#> Importing Astrocyte enhancers ...
#> Importing Astrocyte promoters ...
#> Importing Neuronal enhancers ...
#> Importing Neuronal promoters ...
#> Importing Oligo enhancers ...
#> Importing Oligo promoters ...
#> Importing Microglia enhancers ...
#> Importing Microglia promoters ...
#> Converting dat to GRanges object.
#> ++ NOTT2019:: Getting interaction anchors data.
#> Importing Microglia interactome ...
#> Importing Neuronal interactome ...
#> Importing Oligo interactome ...
#> Converting dat to GRanges object.
#> 29 query SNP(s) detected with reference overlap.
#> Converting dat to GRanges object.
#> 49 query SNP(s) detected with reference overlap.
#> Converting dat to GRanges object.
#> Preparing data for highlighting PLAC-seq interactions that overlap with SNP subset: Support>0
#> Initializing PLAC-seq plot.
#> ++ Adding enhancer/promoter rectangles
#> Creating GWAS track.
#> Creating fine-map track.
#> x_limits will be used to limit the min/max x-axis values for all plots.
#> Converting plots to a merged ggbio Tracks object.
#> Adding vertical track lines for LeadSNP and Consensus_SNP