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| dBUMfit | Function to fit a p-value distribution under beta-uniform mixture model |
| dBUMscore | Function to transform p-values into scores according to the fitted beta-uniform mixture model and/or after controlling false discovery rate |
| dCommSignif | Function to test the significance of communities within a graph |
| dContrast | Function to help build the contrast matrix |
| dDAGannotate | Function to generate a subgraph of a direct acyclic graph (DAG) induced by the input annotation data |
| dDAGinduce | Function to generate a subgraph of a direct acyclic graph (DAG) induced by given vertices |
| dDAGlevel | Function to define/calculate the level of nodes in a direct acyclic graph (DAG) |
| dDAGreverse | Function to reverse the edge direction of a direct acyclic graph (DAG) |
| dDAGroot | Function to find the root node of a direct acyclic graph (DAG) |
| dDAGtip | Function to find the tip node(s) of a direct acyclic graph (DAG) |
| dEnricher | Function to conduct enrichment analysis given the input data and the ontology in query |
| dFDRscore | Function to transform fdr into scores according to log-likelihood ratio between the true positives and the false positivies and/or after controlling false discovery rate |
| dGSEA | Function to conduct gene set enrichment analysis given the input data and the ontology in query |
| dGSEAview | Function to view enrichment results in a sample-specific manner |
| dGSEAwrite | Function to write out enrichment results |
| dNetConfidence | Function to append the confidence information from the source graphs into the target graph |
| dNetFind | Function to find heuristically maximum scoring module |
| dNetInduce | Function to generate a subgraph induced by given vertices and their k nearest neighbors |
| dNetPipeline | Function to setup the pipeline for finding maximum-scoring module from an input graph and the signficance imposed on its nodes |
| dNetReorder | Function to reorder the multiple graph colorings within a sheet-shape rectangle grid |
| dPvalAggregate | Function to aggregate p values |
| dRWR | Function to implement Random Walk with Restart (RWR) on the input graph |
| dSVDsignif | Function to obtain SVD-based gene significance from the input gene-sample matrix |
| visColoralpha | Function to add transparent (alpha) into colors |
| visColormap | Function to define a colormap |
| visDAG | Function to visualise a direct acyclic graph (DAG) with node colorings according to a named input data vector (if provided) |
| visGSEA | Function to visualise running enrichment score for a given sample and a gene set |
| visHeatmap | Function to visualise input data matrix using heatmap |
| visHeatmapAdv | Function to visualise input data matrix using advanced heatmap |
| visNet | Function to visualise a graph object of class "igraph" or "graphNEL" |
| visNetArc | Function to visualise an igraph object via arc diagram |
| visNetCircle | Function to visualise an igraph object via circle diagram |
| visNetMul | Function to visualise the same graph but with multiple graph node colorings according to input data matrix |
| visNetReorder | Function to visualise the multiple graph colorings reorded within a sheet-shape rectangle grid |
| visTreeBootstrap | Function to build and visualise the bootstrapped tree |