Man pages for kpj/dce
Pathway Enrichment Based on Differential Causal Effects

as_adjmatgraph to adjacency
as.data.frame.dceDce to data frame
create_random_DAGCreate random DAG (topologically ordered)
dce-methodsDifferential Causal Effects - main function
dce_nbDifferential Causal Effects for negative binomial data
df_pathway_statisticsBiological pathway information.
estimate_latent_countEstimate number of latent confounders Compute the true casual...
g2dagGraph to DAG
get_pathway_infoDataframe containing meta-information of pathways in database
get_pathwaysEasy pathway network access
get_prediction_countsCompute true positive/... counts
graph2dfGraph to data frame
graph_unionGraph union
pcorPartial correlation
permutation_testPermutation test for (partial) correlation on non-Gaussian...
plot.dcePlot dce object
plot_networkPlot network adjacency matrix
propagate_gene_edgesRemove non-gene nodes from pathway and reconnect nodes
resample_edge_weightsResample network edge weights
rlm_dcecostum rlm function
simulate_data-methodsSimulate data
summary.rlm_dcesummary for rlm_dce
topologically_orderingTopological ordering
trueEffectsCompute the true casual effects of a simulated dag
kpj/dce documentation built on Oct. 29, 2022, 1:40 a.m.