| job.kda | Key Driver Analyzing results | 
| kda2cytoscape | Generate input files for Cytoscape | 
| kda2cytoscape.colorize | Trace module memberships of genes | 
| kda2cytoscape.colormap | Assign one color to each unique module | 
| kda2cytoscape.drivers | Select top key drivers for each module | 
| kda2cytoscape.edges | Find edges of a given node with a specified depth | 
| kda2cytoscape.exec | Evaluate each module separately for visualization | 
| kda2cytoscape.identify | Match identities with respect to given variable name | 
| kda2himmeli | Generate input files for Himmeli | 
| kda2himmeli.colorize | Trace module memberships of genes | 
| kda2himmeli.colormap | Assign one color to each unique module | 
| kda2himmeli.drivers | Select top key drivers for each module | 
| kda2himmeli.edges | Find edges of a given node with a specified depth | 
| kda2himmeli.exec | Evaluate each module separately for visualization | 
| kda2himmeli.identify | Match identities with respect to given variable name | 
| kda.analyze | Weighted key driver analysis (wKDA) main function | 
| kda.analyze.exec | Auxiliary function for weight key driver analysis (wKDA) | 
| kda.analyze.simulate | Weighted key driver analysis (wKDA) simulation | 
| kda.analyze.test | Calculate enrichment score for wKDA | 
| kda.configure | Set parameters for weighted key driver analysis (wKDA) | 
| kda.finish | Organize and save results | 
| kda.finish.estimate | Estimate measures for accomplished wKDA results | 
| kda.finish.save | Save full wKDA results | 
| kda.finish.summarize | Summarize the wKDA results | 
| kda.finish.trim | Trim numbers before save | 
| kda.prepare | Prepare graph topology for weighted key driver analysis | 
| kda.prepare.overlap | Extract overlapping co-hubs | 
| kda.prepare.screen | Prepare hubs and hubnets | 
| kda.start | Import data for weighted key driver analysis | 
| kda.start.edges | Import nodes and edges of graph topology | 
| kda.start.identify | Convert identities to indices for wKDA | 
| kda.start.modules | Import module descriptions | 
| Mergeomics-package | Integrative network analysis of omics data | 
| MSEA.KDA.onestep | Run MSEA and/or KDA in one step | 
| ssea2kda | Generate inputs for wKDA | 
| ssea2kda.analyze | Apply second MSEA after merging the modules | 
| ssea2kda.import | Import genes and top markers from original files | 
| ssea.analyze | Marker set enrichment analysis (MSEA) | 
| ssea.analyze.observe | Collect enrichment score statistics for MSEA | 
| ssea.analyze.randgenes | Estimate enrichment from randomized genes | 
| ssea.analyze.randloci | Estimate enrichment from randomized marker | 
| ssea.analyze.simulate | Simulate scores for MSEA | 
| ssea.analyze.statistic | MSEA statistics for enrichment score | 
| ssea.control | Add internal positive control modules for MSEA | 
| ssea.finish | Organize and save MSEA results | 
| ssea.finish.details | Organize and save module, gene, top locus, Ps of MSEA results | 
| ssea.finish.fdr | Organize and save FDR results of the MSEA | 
| ssea.finish.genes | Organize and save gene-realted MSEA results | 
| ssea.meta | Merge multiple MSEA results into meta MSEA | 
| ssea.prepare | Prepare an indexed database for MSEA | 
| ssea.prepare.counts | Calculate hit counts up to a given quantile | 
| ssea.prepare.structure | Construct hierarchical representation of components | 
| ssea.start | Create a job for MSEA | 
| ssea.start.configure | Check parameters before MSEA | 
| ssea.start.identify | Convert identities to indices for MSEA | 
| ssea.start.relabel | Update gene symbols after merging overlapped markers | 
| tool.aggregate | Aggregate the entries | 
| tool.cluster | Hierarchical clustering of nodes | 
| tool.cluster.static | Static hierarchical clustering | 
| tool.coalesce | Calculate overlaps between groups (main function) | 
| tool.coalesce.exec | Find, merge, and trim overlapping clusters | 
| tool.coalesce.find | Find overlapping clusters | 
| tool.coalesce.merge | Merge overlapping clusters | 
| tool.fdr | Estimate False Discovery Rates (FDR) | 
| tool.fdr.bh | Benjamini and Hochberg False Discovery Rate | 
| tool.fdr.empirical | Estimate Empirical False Discovery Rates | 
| tool.graph | Convert an edge list to a graph representation | 
| tool.graph.degree | Find degrees of the nodes | 
| tool.graph.list | Return edge list for each node | 
| tool.metap | Estimate meta P-values | 
| tool.normalize | Estimate statistical scores based on Gauss distribution | 
| tool.normalize.quality | Check normalization quality | 
| tool.overlap | Calculate overlaps between groups of specified items | 
| tool.read | Read a data frame from a file | 
| tool.save | Save a data frame in tab-delimited file | 
| tool.subgraph | Determine network neighbors for a set of nodes | 
| tool.subgraph.find | Find edges to adjacent nodes | 
| tool.subgraph.search | Search neighborhoods for given nodes | 
| tool.subgraph.stats | Calculate node degrees and strengths | 
| tool.translate | Translate gene symbols | 
| tool.unify | Convert a distribution to uniform ranks | 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.