metavariable_info: Compute Metavariable Information

Description

Calculates attributes for each node in a graph object pertaining to their suitability and rank as metavariables; primarily if they are the most informative common ancestor (see node_IC_zhou) of a set of nodes representing a dataset variable.

Usage

metavariable_info(graph, mode = "in", IC_threshold = 0)

Value

A modified graph object with additional node attributes pertaining to their status as a metavariable.

Arguments

graph: Graph containing ontological and dataset nodes. Must be in tidygraph format or coercible to this format.
mode: Character constant specifying the directionality of the edges. One of: "in" or "out".
IC_threshold: Metavariables with IC less than this value will be omitted from output. Default = 0 (no omission).

Details

The added attributes are:

is_metavariable: Logical. If the node has at least two descendants in the graph which represent dataset variables.
variable_descendants: List. The names of variables of which a node is an ancestor.
variable_set: Integer. An identifier for the unique set of descendants in the graph which represent dataset variables. The assigned number corresponds to the order in which a unique set was identified when scanning through the node table.
highest_IC: Logical. If the node possesses the highest information content of all other nodes which are common ancestors of the same variable set. Information content is expected to have been calculated in join_vars_to_ontol.

Examples

Run this code

data(example_ontology)
require(magrittr)
example_ontology %>%
join_vars_to_ontol(example_mapping_file, root = "root") -> joined_ontol

metavariable_info(joined_ontol)