enrichment {pathfindR} | R Documentation |
Perform Enrichment Analysis for a Single Gene Set
Description
Perform Enrichment Analysis for a Single Gene Set
Usage
enrichment(
input_genes,
genes_by_term = pathfindR.data::kegg_genes,
term_descriptions = pathfindR.data::kegg_descriptions,
adj_method = "bonferroni",
enrichment_threshold = 0.05,
sig_genes_vec,
background_genes
)
Arguments
input_genes |
The set of gene symbols to be used for enrichment analysis. In the scope of this package, these are genes that were identified for an active subnetwork |
genes_by_term |
List that contains genes for each gene set. Names of this list are gene set IDs (default = kegg_genes) |
term_descriptions |
Vector that contains term descriptions for the gene sets. Names of this vector are gene set IDs (default = kegg_descriptions) |
adj_method |
correction method to be used for adjusting p-values. (default = 'bonferroni') |
enrichment_threshold |
adjusted-p value threshold used when filtering enrichment results (default = 0.05) |
sig_genes_vec |
vector of significant gene symbols. In the scope of this package, these are the input genes that were used for active subnetwork search |
background_genes |
vector of background genes. In the scope of this package,
the background genes are taken as all genes in the PIN
(see |
Value
A data frame that contains enrichment results
See Also
p.adjust
for adjustment of p values. See
run_pathfindR
for the wrapper function of the pathfindR
workflow. hyperg_test
for the details on hypergeometric
distribution-based hypothesis testing.
Examples
enrichment(
input_genes = c('PER1', 'PER2', 'CRY1', 'CREB1'),
sig_genes_vec = 'PER1',
background_genes = unlist(pathfindR.data::kegg_genes)
)