
GO, KEGG, and Reactome over-representation analysis (ORA)
gly_enrich_go.Rd
Perform GO, KEGG, and Reactome ORA for proteins/genes.
Usage
gly_enrich_go(exp, add_info = TRUE, ...)
gly_enrich_go_(proteins, ...)
gly_enrich_kegg(exp, add_info = TRUE, ...)
gly_enrich_kegg_(proteins, ...)
gly_enrich_reactome(exp, add_info = TRUE, ...)
gly_enrich_reactome_(proteins, ...)
Arguments
- exp
A
glyexp::experiment()
object.- add_info
A logical value. This parameter is included for API consistency but has no effect since enrichment results do not contain variable or sample columns. Only applicable to top-level APIs.
- ...
Additional arguments passed to
clusterProfiler::enrichGO()
,clusterProfiler::enrichKEGG()
, orReactomePA::enrichPathway()
.- proteins
A character vector of UniProt accession IDs.
Value
A list with two elements:
tidy_result
: A tibble with enrichment results containing the following columns:id
: Term ID (GO:XXXXXXX, hsa:XXXXX, or R-HSA-XXXXX)description
: Term descriptiongene_ratio
: Ratio of genes in the term to total genes in the inputbg_ratio
: Ratio of genes in the term to total genes in the backgroundp_value
: Raw p-value from hypergeometric testp_adjust
: Adjusted p-valueq_value
: Q-value (FDR)gene_id
: Gene IDs in the term (separated by "/")count
: Number of genes in the term
raw_result
: The raw clusterProfiler enrichResult object The list has classesglystats_go_ora_res
/glystats_kegg_ora_res
/glystats_reactome_ora_res
andglystats_res
.
Details
These functions perform over-representation analysis using the specified database.
gly_enrich_go()
, gly_enrich_kegg()
, and gly_enrich_reactome()
are the top-level APIs
that work with glyexp::experiment()
objects and extract protein information automatically
from the "protein" column in the variable information tibble.
gly_enrich_go_()
, gly_enrich_kegg_()
, and gly_enrich_reactome_()
are the underlying APIs
that work with protein vectors directly, providing more flexibility for users who don't use the glyexp package.
Gene Extraction (top-level APIs only): Proteins are extracted from the experiment's variable information. The function looks for columns containing protein identifiers and uses them for enrichment analysis. Protein identifiers should be UniProt accessions.
GO Analysis:
Uses clusterProfiler::enrichGO()
with UniProt IDs as input.
KEGG Analysis:
Uses clusterProfiler::enrichKEGG()
with UniProt IDs as input.
Reactome Analysis:
Converts UniProt IDs to Entrez IDs and uses ReactomePA::enrichPathway()
.