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| Mergeomics-package | Integrative network analysis of omics data |
| job.kda | Key Driver Analyzing results |
| 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 |
| 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 |
| Mergeomics | Integrative network analysis of omics data |
| MSEA.KDA.onestep | Run MSEA and/or KDA in one step |
| 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 |
| ssea2kda | Generate inputs for wKDA |
| ssea2kda.analyze | Apply second MSEA after merging the modules |
| ssea2kda.import | Import genes and top markers from original files |
| 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 |