deepblue_enrich_regions_overlap {DeepBlueR} | R Documentation |
Enrich the regions based on regions overlap analysis.
deepblue_enrich_regions_overlap(query_id = NULL, background_query_id = NULL, datasets = NULL, genome = NULL, user_key = deepblue_options("user_key"))
query_id |
- A string (Query ID) |
background_query_id |
- A string (query_id containing the regions that will be used as the background data.) |
datasets |
- A struct (a map where each key is an identifier and the value is a list containing experiment names or query_ids (you can use both together).) |
genome |
- A string (the target genome) |
user_key |
- A string (users token key) |
request_id - A string (Request ID - Use it to retrieve the result with info() and get_request_data(). The result is a list containing the datasets that overlap with the query_id regions.)
Other Enrich the genome regions: deepblue_enrich_regions_fast
,
deepblue_enrich_regions_go_terms
query_id = deepblue_select_experiments( experiment_name="S00VEQA1.hypo_meth.bs_call.GRCh38.20150707.bed") filtered_query_id = deepblue_filter_regions( query_id = query_id, field = "AVG_METHYL_LEVEL", operation = "<", value = "0.0025", type="number") rg_10kb_tilling = deepblue_tiling_regions( size = 1000, genome = "hg19") # We could have included more Epigenetic Marks here epigenetic_marks <- c("h3k27ac", "H3K27me3", "H3K4me3") histones_datasets = c() for (i in 1:length(epigenetic_marks)) { experiments_list <- deepblue_list_experiments( epigenetic_mark=epigenetic_marks[[i]], type="peaks", genome="grch38", project="BLUEPRINT Epigenome"); experiment_names = deepblue_extract_names(experiments_list) histones_datasets[[epigenetic_marks[[i]]]] = experiment_names } deepblue_enrich_regions_overlap( query_id=filtered_query_id, background_query=rg_10kb_tilling, datasets=histones_datasets, genome="grch38")