wpLogicNet

library(wpLogicNet)

logic gate and structure inference

expression_data<- data_normalization(data$SOS1)

res <- wpLogicNet(data = expression_data, density = "laplace", scale = 0.00071, number_of_em_iterations = 15, BF_threshold = 11)

expression_data<- data_normalization(data$SOS2)

res <- wpLogicNet(data = expression_data, density = "laplace", scale = 0.00011, number_of_em_iterations = 15, BF_threshold = 4)

expression_data<- data$Y2

res <- wpLogicNet(data = expression_data, density = "laplace", scale = 0.00021, number_of_em_iterations = 15, BF_threshold = 4)

expression_data<- data$Y3

res <- wpLogicNet(data = expression_data, density = "logis", scale = 0.0002, number_of_em_iterations = 10, BF_threshold = 3)

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logic gate inference in structure-aware mode

expression_data<- data_normalization(data$SOS1)

res <- wpLogicNet_structure_aware(data = expression_data, density = "norm", scale = 10^-3, true_edges = true_edges$SOS1, number_of_em_iterations = 10)

predicted_gates<- res$predicted_gates

a_posteriori_distributed_sample<- res$a_posteriori_distributed_sample ################################################################################