Description Usage Arguments Details Value Examples
View source: R/aop_graph_analysis.R
Performs a backdoor causal network analysis to idenitfy nodes/key events which are sufficient to infer causality.
1 | aop_backdoor(aop_graph, ke_coord, ao_coord, measureable_nodes = NULL)
|
aop_graph |
a |
ke_coord |
typically this is the molecular initiating event node, but really, this is any node that you want as the starting/source point. For instance, this is normally the point at which exposure to a stressor is going to enter the AOP. |
ao_coord |
typically this is the adverse outcome node. |
measureable_nodes |
this param is not used yet. In the future this node
will be a |
This function performs Pearl's backdoor analysis. Whereas Pearl was interested in identifying nodes which need to be measured to make a causal statement, we are interested in identifying those nodes/key events which need to measured to say that an adverse outcome is likely to occur. It's essentially the same thing as Pearl, only a slightly different interpretation.
causal_nodes vector
a vector of the names of the causal nodes.
1 2 3 4 5 | steatosis_json_file <- system.file("extdata", "steatosis_aop_json.cyjs",
package = "aop")
steatosis_aop <- convert_cytoscape_to_aop(steatosis_json_file)
steatosis_aop_graph <- convert_aop_to_graph(steatosis_aop)
aop_backdoor(steatosis_aop_graph, "391", "388")
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