Plot enrichment results from XGR annotations.
XGR_enrichment_plot(
enrich_res,
title = NULL,
subtitle = NULL,
facet_formula = NULL,
line_formula = "y ~ x",
line_method = "lm",
line_span = 1,
FDR_thresh = 1,
plot_type = "bar",
shape_var = "Cell_type",
facet_scales = "free",
show_plot = TRUE,
save_plot = FALSE,
height = 5,
width = 5,
dpi = 300
)
Plot resolution. Also accepts a string input: "retina" (320), "print" (300), or "screen" (72). Applies only to raster output types.
Other XGR:
XGR_enrichment_bootstrap()
,
XGR_enrichment()
,
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
if (FALSE) {
root <- file.path(
"/sc/arion/projects/pd-omics/brian",
"Fine_Mapping/Data/GWAS/Nalls23andMe_2019/_genome_wide"
)
### merged enrichment results
enrich_res <- data.table::fread(
file.path(
root,
"XGR/celltypespecific_epigenomics.SNP_groups.csv.gz"
)
)
enrich_res <- data.table::fread(
file.path(
root,
"XGR/celltypespecific_epigenomics.snp_groups.csv.gz"
)
)
enrich_boot <- data.table::fread(
file.path(
root,
"XGR/celltypespecific_epigenomics.snp_groups.permute.csv.gz"
)
)
enrich_assay <- data.table::fread(
file.path(
root,
"XGR/celltypespecific_epigenomics.snp_groups.assay.csv.gz"
)
)
# Merged volcano plot
enrich_res <- subset(enrich_res, SNP_Group != "Consensus (-PolyFun)") |>
dplyr::rename(SNP_group = SNP_Group)
gp <- XGR_enrichment_plot(
enrich_res = subset(enrich_res, !Assay %in% c("HiChIP_FitHiChIP", "PLAC")),
title = "Enrichment: Cell-type-specific epigenomics",
plot_type = "point",
save_plot = file.path(
root, "XGR/celltypespecific_epigenomics.enrich_volcano.png"
),
height = 6, width = 8, shape_var = "Assay"
)
## Merged bar plot
gp <- XGR_enrichment_plot(
enrich_res = enrich_res,
plot_type = "bar",
facet_formula = ".~Assay",
FDR_thresh = .05
)
# Merged volcano plot (permuted)
gp <- XGR_enrichment_plot(
enrich_res = enrich.scATAC.permute,
title = "Permuted enrichment: Cell-type-specific peaks and elements",
plot_type = "point"
)
}