NOTT2019_get_interactome: Import cell type-specific interactomes

In RajLabMSSM/echoannot: echoverse module: Annotate fine-mapping results

Import cell type-specific interactomes

Description

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

Usage

NOTT2019_get_interactome(
  annot_sub,
  top.consensus.pos,
  marker_key = NOTT2019_marker_key(),
  verbose = TRUE
)

Arguments

annot_sub	annot_sub
top.consensus.pos	Top Consensus SNP position.
marker_key	Marker key.
verbose	Print messages.

Source

Nott et al. (2019)

See Also

Other NOTT2019: NOTT2019_bigwig_metadata, NOTT2019_epigenomic_histograms(), NOTT2019_get_epigenomic_peaks(), NOTT2019_get_interactions(), 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

dat <- echodata::BST1
annot_sub <- NOTT2019_get_promoter_interactome_data(dat = dat)
interact.DT <- NOTT2019_get_interactome(annot_sub=annot_sub, 
                                        top.consensus.pos = 15712787)

RajLabMSSM/echoannot documentation built on Oct. 26, 2023, 2:41 p.m.