Given a tbl_kgx graph, retrieve the last-used engine.
get_engine(g, fail_if_missing = TRUE)A graph engine object.
# Using example KGX file packaged with monarchr
filename <- system.file("extdata", "eds_marfan_kg.tar.gz", package = "monarchr")
g <- file_engine(filename) |>
fetch_nodes(query_ids = c("MONDO:0007525", "MONDO:0007526"))
print(get_engine(g))
#> $name
#> [1] "file_engine"
#>
#> $preferences
#> $preferences$category_priority
#> [1] "biolink:Disease" "biolink:PhenotypicFeature"
#> [3] "biolink:Gene" "biolink:AnatomicalEntity"
#> [5] "biolink:BiologicalProcess" "biolink:Pathway"
#> [7] "biolink:Cell" "biolink:CellularComponent"
#> [9] "biolink:ChemicalEntity" "biolink:Drug"
#>
#> $preferences$node_property_priority
#> [1] "id" "pcategory" "name" "symbol"
#> [5] "in_taxon_label" "description" "synonym"
#>
#> $preferences$edge_property_priority
#> [1] "subject" "predicate" "object"
#>
#>
#> $filename
#> [1] "/__w/_temp/Library/monarchr/extdata/eds_marfan_kg.tar.gz"
#>
#> $graph
#> # A tbl_graph: 3000 nodes and 7148 edges
#> #
#> # A directed acyclic multigraph with 1 component
#> #
#> # Node Data: 3,000 × 16 (active)
#> id name symbol in_taxon_label description synonym category iri xref
#> <chr> <chr> <chr> <chr> <chr> <list> <list> <chr> <lis>
#> 1 MONDO:0… Marf… NA NA A disorder… <chr> <chr> http… <chr>
#> 2 MONDO:0… Ehle… NA NA The Ehlers… <chr> <chr> http… <chr>
#> 3 MONDO:0… Ehle… NA NA Ehlers-Dan… <chr> <chr> http… <chr>
#> 4 MONDO:0… ehle… NA NA NA <chr> <chr> http… <chr>
#> 5 MONDO:0… Beth… NA NA NA <chr> <chr> http… <chr>
#> 6 MONDO:0… Ehle… NA NA A form of … <chr> <chr> http… <chr>
#> 7 MONDO:0… Ehle… NA NA A form of … <chr> <chr> http… <chr>
#> 8 MONDO:0… brit… NA NA Brittle co… <chr> <chr> http… <chr>
#> 9 MONDO:0… brit… NA NA Any brittl… <chr> <chr> http… <chr>
#> 10 MONDO:0… comb… NA NA NA <chr> <chr> http… <chr>
#> # ℹ 2,990 more rows
#> # ℹ 7 more variables: namespace <chr>, provided_by <chr>, in_taxon <chr>,
#> # full_name <chr>, type <list>, has_gene <chr>, pcategory <chr>
#> #
#> # Edge Data: 7,148 × 25
#> from to subject predicate object agent_type knowledge_level
#> <int> <int> <chr> <chr> <chr> <chr> <chr>
#> 1 3 2 MONDO:0009159 biolink:subclass_… MONDO… not_provi… not_provided
#> 2 4 2 MONDO:0040501 biolink:subclass_… MONDO… not_provi… not_provided
#> 3 5 2 MONDO:0034022 biolink:subclass_… MONDO… not_provi… not_provided
#> # ℹ 7,145 more rows
#> # ℹ 18 more variables: knowledge_source <chr>,
#> # aggregator_knowledge_source <chr>, primary_knowledge_source <chr>,
#> # provided_by <chr>, id <chr>, category <chr>, original_object <chr>,
#> # original_subject <chr>, frequency_qualifier <chr>, has_evidence <chr>,
#> # has_total <dbl>, has_quotient <dbl>, has_count <dbl>, has_percentage <dbl>,
#> # onset_qualifier <chr>, publications <chr>, qualifiers <chr>, …
#>
#> attr(,"class")
#> [1] "file_engine" "base_engine" "list"