evaluate_network: Evaluates an inferred network against validated regulatory...

In OceaneCsn/AraNetBench: Evaluates an inferred regulatory network against state of the art interaction databases in Arabidopsis thaliana

Evaluates an inferred network against validated regulatory interactions

Description

Evaluates an inferred network against validated regulatory interactions

Usage

evaluate_network(
  net,
  validation = c("CHIPSeq", "DAPSeq", "TARGET"),
  subset_validated_edges = NULL
)

Arguments

net	dataframe with a column 'from' (regulators) and a column 'to' (targets), representing the inferred network of edges to evaluate
validation	type of edge in the validation database that should be considered to defined a true/supported prediction in the evaluation process. The validation type must be a vector of one or more of the following values : CHIPSeq, DAPSeq, Litterature, TARGET
subset_validated_edges	potential dataframe of validated edges (that should however contain all the nodes in the inferred network). Made to speed up computation in ROC and test again random.

Value

a list containing true positives, true positive rate, false positives, false positive rate, and the input network dataframe with an additional column to caracterise how is the edge supported by known interactions

Examples

#' data("abiotic_stress_Heat_genes_net")
set.seed(999)
results <- evaluate_network(abiotic_stress_Heat_genes_net)
results[c("tp", "fp", "tpr", "fpr")]

OceaneCsn/AraNetBench documentation built on May 22, 2022, 12:43 p.m.