run_congenital_enrichment: Run congenital enrichment analyses

In neurogenomics/MultiEWCE: Multi-Scale Target Explorer

Run congenital enrichment analyses

Description

First, this function computes the mean difference in association p-values between a given phenotype and the congenital and non-congenital versions of a cell type (the fetal_nonfetal_pdiff column). It then sorts the results from the largest to the smallest difference. Here, a positive difference indicates that the phenotype is more associated with the fetal/embryonic version of the cell type, while a negative difference indicates that the phenotype is more associated with the adult version. Next, it runs enrichment analyses for the top and bottom N phenotypes using the dag_enrich_on_offsprings function. Finally, it run enrichment analyses for the top and bottom N cell types.

Usage

run_congenital_enrichment(
  results,
  hpo = HPOExplorer::get_hpo(),
  cl = KGExplorer::filter_ontology(KGExplorer::get_ontology("cl"), keep_descendants =
    "cell"),
  gpt_annot = HPOExplorer::gpt_annot_codify(),
  fetal_keywords = c("fetal", "fetus", "primordial", "hESC", "embryonic"),
  celltype_col = "author_celltype",
  top_n_phenotypes = 10,
  top_n_hpo = 50,
  top_n_cl = top_n_hpo,
  q_threshold = 0.05,
  prune = TRUE,
  ...
)

Arguments

results	The cell type-phenotype enrichment results generated by gen_results and merged together with merge_results
hpo	Human Phenotype Ontology object, loaded from get_ontology.
cl	Cell Ontology (CL) object from KGExplorer::get_ontology("cl").
gpt_annot	A data.table of GPT annotations.
fetal_keywords	A character vector of keywords to identify fetal cell types.
celltype_col	The column name of the cell type.
top_n_phenotypes	Number of top and bottom phenotypes to return.
top_n_hpo	Number of top and bottom phenotypes to run enrichment analyses on.
top_n_cl	Number of top and bottom cell types to run enrichment analyses on.
q_threshold	The q value threshold to subset the results by.
prune	Prune redundant ancestral terms from the enrichment results using prune_ancestors.
...	Arguments passed on to simona::dag_enrich_on_offsprings dag An ontology_DAG object. terms A vector of term names. min_hits Minimal number of terms in an offspring set. min_offspring Minimal size of the offspring set.

Value

Named list of enrichment results.

Examples

results <- load_example_results()[ctd=="HumanCellLandscape"]
out <- run_congenital_enrichment(results=results)

neurogenomics/MultiEWCE documentation built on Aug. 24, 2024, 1:41 a.m.