as.data.frame.dce       Dce to data frame
as_adjmat               graph to adjacency
create_random_DAG       Create random DAG (topologically ordered)
dce                     Differential Causal Effects - main function
dce_nb                  Differential Causal Effects for negative
                        binomial data
df_pathway_statistics   Biological pathway information.
estimate_latent_count   Estimate number of latent confounders Compute
                        the true casual effects of a simulated dag
g2dag                   Graph to DAG
get_pathway_info        Dataframe containing meta-information of
                        pathways in database
get_pathways            Easy pathway network access
get_prediction_counts   Compute true positive/... counts
graph2df                Graph to data frame
graph_union             Graph union
pcor                    Partial correlation
permutation_test        Permutation test for (partial) correlation on
                        non-Gaussian data
plot.dce                Plot dce object
plot_network            Plot network adjacency matrix
propagate_gene_edges    Remove non-gene nodes from pathway and
                        reconnect nodes
resample_edge_weights   Resample network edge weights
rlm_dce                 costum rlm function
simulate_data           Simulate data
summary.rlm_dce         summary for rlm_dce
topologically_ordering
                        Topological ordering
trueEffects             Compute the true casual effects of a simulated
                        dag
