Knowledge Graph edge weights

Source: R/kg_edge_weights.R

Compute edge weights for the given tbl_kgx graph using several pieces of categorical, ordinal, and continuous metadata.

kg_edge_weights(
  graph,
  normalise = TRUE,
  encodings = monarch_edge_weight_encodings(),
  fun = function(x) {
     rowSums(x, na.rm = TRUE)
 }
)

Arguments

graph

A graph object

normalise

Normalise each encoding from 0-1 by dividing by the maximum value. Default is TRUE.

encodings

A list of named lists of encoding values for different edge attributes.

fun

Function to compute edge weights with across the numerically encoded attributes. Default is rowSums.

Examples

filename <- system.file("extdata", "eds_marfan_kg.tar.gz", package = "monarchr")
g <- file_engine(filename) |>
          fetch_nodes(query_ids = "MONDO:0007525") |>
          expand(predicates = "biolink:has_phenotype",
                 categories = "biolink:PhenotypicFeature")|>
          expand(categories = "biolink:Gene")
g2 <- kg_edge_weights(g)
edges(g2)$weight
#>  [1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#> [39] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2