Run fgsea simple method for gene ontology with elimination method

Usage

rs_geom_elim_fgsea_simple(
  stats,
  levels,
  go_obj,
  gsea_params,
  elim_threshold,
  iters,
  seed
)

stats

Named numerical vector. Needs to be sorted. The gene level statistics.

levels

A character vector representing the levels to iterate through. The order will be the one the iterations are happening in.

go_obj

The gene_ontology_data S7 class. See gene_ontology_data().

gsea_params

List. The GSEA parameters, see params_gsea() wrapper function. This function generates a list containing:

min_size - Integer. Minimum size for the gene sets.
max_size - Integer. Maximum size for the gene sets.
gsea_param - Float. The GSEA parameter. Defaults to 1.0.
sample_size - Integer. Number of samples to iterate through for the multi-level implementation of fgsea.
eps - Float. Boundary for calculating the p-value. Used for the multi- level implementation of fgsea.

elim_threshold

p-value below which the elimination procedure shall be applied to the ancestors.

iters

Integer. Number of random permutations for the fgsea simple method to use

seed

Integer. For reproducibility purposes.

List with the following elements

go_ids The name of the tested gene ontology identifer.
es The enrichment scores for the pathway
nes The normalised enrichment scores for the pathway
size The pathway sizes (after elimination!).
pvals The p-values for this pathway based on permutation testing
n_more_extreme Number of times the enrichment score was bigger or smaller than the permutation (pending sign).
le_zero Number of times the permutation was less than zero.
ge_zero Number of times the permutation was greater than zero.
leading_edge A list of the index positions of the leading edge genes for this given GO term.