Pathway Enrichment Based on Differential Causal Effects

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Documentation for package ‘dce’ version 1.8.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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-method	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_pathways	Easy pathway network access
get_pathway_info	Dataframe containing meta-information of pathways in database
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
simulate_data-method	Simulate data
summary.rlm_dce	summary for rlm_dce
topologically_ordering	Topological ordering
trueEffects	Compute the true casual effects of a simulated dag