03 Pathway Genes

Building the Pathway-Gene Map

There are two ways to build the pathway-gene mapping required by pathway_dsge(): GAF files (mode A) or Bioconductor OrgDb (mode B). Both produce the same named-list output format.

Mode A: get_pathway_genes()

Splits a GAF table into a named list by GO term. Each element is a data.frame of genes in that pathway.

pw <- get_pathway_genes(
  gaf,
  genes     = c("db_object_id", "db_object_symbol"),
  unique    = TRUE,
  min_size  = 5,
  qualifier = NULL,
  evidence  = NULL,
  aspect    = NULL,
  go_names  = go
)

Parameters

Parameter	Default	Description
gaf_data	(required)	Output of read_gaf()
genes	c("db_object_id", "db_object_symbol")	Columns kept for downstream matching
unique	TRUE	Remove duplicate gene entries per term
min_size	5	Discard pathways below this gene count
qualifier	NULL	Filter by GAF qualifier (e.g. "enables", "involved_in")
evidence	NULL	Filter by evidence code (e.g. c("IDA", "IPI"))
aspect	NULL	Filter by ontology: "P" (BP), "F" (MF), "C" (CC)
go_names	NULL	Output of read_obo() — adds gs_name, gs_source columns

Mode B: get_pathway_genes_db()

An alternative that uses Bioconductor's OrgDb packages, avoiding the need for GAF + OBO files.

Common model organisms

library(org.Hs.eg.db)    # human
library(org.Mm.eg.db)    # mouse
library(org.Dr.eg.db)    # zebrafish
library(org.Rn.eg.db)    # rat
library(org.Dm.eg.db)    # fruit fly
library(org.Ce.eg.db)    # C. elegans
library(org.Sc.sgd.db)   # yeast
library(org.At.tair.db)  # Arabidopsis

pw <- get_pathway_genes_db(org.Hs.eg.db)

Non-model organisms via AnnotationHub

library(AnnotationHub)
hub <- AnnotationHub()
query(hub, "Ovis aries")               # search for sheep
sheep_orgdb <- hub[["AH72269"]]        # load the OrgDb

pw <- get_pathway_genes_db(sheep_orgdb)

Parameters

Parameter	Default	Description
orgdb	(required)	An OrgDb object (e.g., org.Hs.eg.db)
keytype	"ENTREZID"	Key type for gene IDs in the OrgDb
gene_id_col	"db_object_id"	Gene ID column name in output
gene_symbol_col	"db_object_symbol"	Gene symbol column name in output
min_size	5	Drop pathways below this gene count
aspect	NULL	Ontology filter: "BP", "MF", "CC", or NULL (all)
evidence	NULL	Evidence code filter (e.g., "IDA"); NULL = all
attach_names	TRUE	Fetch pathway names (requires GO.db)
use_goall	FALSE	If TRUE, propagate annotations to all ancestor GO terms (broader pathway set, consistent with clusterProfiler default)

Mode C: get_pathway_genes_kegg()

Extracts KEGG pathway annotations from an OrgDb's PATH column, with online name lookup via KEGGREST.

Usage

library(org.Hs.eg.db)

# Human KEGG pathways (auto-detects organism)
pw_kegg <- get_pathway_genes_kegg(org.Hs.eg.db, min_size = 5L)

# Mouse
library(org.Mm.eg.db)
pw_kegg <- get_pathway_genes_kegg(org.Mm.eg.db, min_size = 5L)

Parameters

Parameter	Default	Description
orgdb	(required)	An OrgDb object
keytype	"ENTREZID"	Key type for querying the OrgDb
gene_id_col	"kegg_gene_id"	Gene ID column name in output
gene_symbol_col	"kegg_gene_symbol"	Gene symbol column name in output
min_size	5	Drop pathways below this gene count
attach_path_names	TRUE	Fetch pathway names via KEGGREST::keggList() (requires network)

Output format

str(pw_kegg[[1]])
# Classes 'kegg_pathway' and 'data.frame':  65 obs. of  4 variables:
#  $ kegg_name       : chr  "Glycolysis / Gluconeogenesis - Homo sapiens (human)"
#  $ organism_code   : chr  "hsa"
#  $ kegg_gene_id    : chr  "124" "125" "126" ...
#  $ kegg_gene_symbol: chr  "ADH1A" "ADH1B" "ADH1C" ...

KEGG pathway IDs (list names) include the organism prefix, e.g. "hsa00010".

Supported organisms

The built-in KEGG_ORG_CODES table covers 15 common species — auto-detected from the OrgDb via AnnotationDbi::species().

Species	Code	OrgDb
Human	hsa	org.Hs.eg.db
Mouse	mmu	org.Mm.eg.db
Rat	rno	org.Rn.eg.db
Zebrafish	dre	org.Dr.eg.db
Fruit fly	dme	org.Dm.eg.db
C. elegans	cel	org.Ce.eg.db
Yeast	sce	org.Sc.sgd.db
Arabidopsis	ath	org.At.tair.db
Pig	ssc	org.Ss.eg.db
Cow	bta	org.Bt.eg.db
Dog	cfa	org.Cf.eg.db
Rhesus macaque	mcc	org.Mmu.eg.db
Chicken	gga	org.Gg.eg.db
Frog	xtr	org.Xt.eg.db

Requirements

BiocManager::install(c("KEGGREST", "AnnotationDbi"))

Mode D: get_pathway_genes_reactome()

Extracts Reactome pathway annotations via reactome.db (local, no network needed) and resolves gene symbols from an OrgDb.

Usage

library(org.Hs.eg.db)

# Human Reactome pathways
pw_react <- get_pathway_genes_reactome(org.Hs.eg.db, min_size = 5L)

# Mouse Reactome
library(org.Mm.eg.db)
pw_react <- get_pathway_genes_reactome(org.Mm.eg.db, species_prefix = "R-MMU")

Parameters

Parameter	Default	Description
orgdb	(required)	An OrgDb object (for gene symbol resolution)
keytype	"ENTREZID"	Key type for querying the OrgDb
gene_id_col	"reactome_gene_id"	Gene ID column name in output
gene_symbol_col	"reactome_gene_symbol"	Gene symbol column name in output
min_size	5	Drop pathways below this gene count
attach_path_names	TRUE	Fetch pathway names from reactome.db (local, no network)
species_prefix	"R-HSA"	Reactome species prefix; NULL = all species

Output format

str(pw_react[[1]])
# Classes 'reactome_pathway' and 'data.frame':  96 obs. of  3 variables:
#  $ reactome_name       : chr  "Signaling by Interleukins"
#  $ reactome_gene_id    : chr  "1" "2" "3" ...
#  $ reactome_gene_symbol: chr  "A1BG" "A2M" "A2MP1" ...

Common species prefixes

Species	Prefix	OrgDb
Human	R-HSA	org.Hs.eg.db
Mouse	R-MMU	org.Mm.eg.db
Rat	R-RNO	org.Rn.eg.db
Zebrafish	R-DRE	org.Dr.eg.db
Fly	R-DME	org.Dm.eg.db
Worm	R-CEL	org.Ce.eg.db

Requirements

BiocManager::install(c("reactome.db", "AnnotationDbi"))