XGR enrichment

Run SNP-level enrichment test with xGRviaGenomicAnno.

XGR_enrichment(
  gr,
  merged_dat,
  foreground_filter = "Consensus_SNP==TRUE",
  background_filter = NULL,
  grouping_vars = c("Study", "Assay", "Cell_type"),
  fg_sample_size = NULL,
  bg_sample_size = NULL,
  background.annotatable.only = FALSE,
  verbose = TRUE
)

Arguments

gr

Annotations to test for enrichment with.

merged_dat

SNP-level fine-mapping results to test for enrichment with.

foreground_filter

Filter to apply to foreground (target SNPs).

background_filter

Filter to apply to background (non-target SNPs).

grouping_vars

Columns in merged_dat to group by when conducting enrichment tests.

fg_sample_size

Foreground sample size.

bg_sample_size

Background sample size.

background.annotatable.only

For background SNPs, only use SNPs that overlap with some annotation in gr. This means that missing annotations (NA) will not be considered.

verbose

Print messages.

See also

Other XGR: XGR_enrichment_bootstrap(), XGR_enrichment_plot(), XGR_filter_assays(), XGR_filter_sources(), XGR_import_annotations(), XGR_iterate_enrichment(), XGR_iterate_overlap(), XGR_merge_and_process(), XGR_parse_metadata(), XGR_plot_enrichment(), XGR_prepare_foreground_background(), XGR_query(), XGR_sep_handler(), xgr_example

Examples

if (FALSE) {
gr.merged <- echoannot::merge_celltype_specific_epigenomics()
enrich.lead <- XGR_enrichment(
    gr = gr.merged,
    merged_dat = echodata::get_Nalls2019_merged(),
    foreground_filter = "leadSNP==TRUE",
    grouping_vars = c("Study", "Cell_type", "Assay")
)
}