Mergeomics: Integrative network analysis of omics data

The Mergeomics pipeline serves as a flexible framework for integrating multidimensional omics-disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. It includes two main parts, 1) Marker set enrichment analysis (MSEA); 2) Weighted Key Driver Analysis (wKDA).

Install the latest version of this package by entering the following in R:
AuthorVille-Petteri Makinen, Le Shu, Yuqi Zhao, Zeyneb Kurt, Bin Zhang, Xia Yang
Bioconductor views Software
Date of publicationNone
MaintainerZeyneb Kurt <>
LicenseGPL (>= 2)

View on Bioconductor

Man pages

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 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) Benjamini and Hochberg False Discovery Rate

tool.fdr.empirical: Estimate Empirical False Discovery Rates

tool.graph: Convert an edge list to a graph representation 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 Read a data frame from a file 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 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


job.kda Man page
kda2cytoscape Man page
kda2cytoscape.colorize Man page
kda2cytoscape.colormap Man page
kda2cytoscape.drivers Man page
kda2cytoscape.edges Man page
kda2cytoscape.exec Man page
kda2cytoscape.identify Man page
kda2himmeli Man page
kda2himmeli.colorize Man page
kda2himmeli.colormap Man page
kda2himmeli.drivers Man page
kda2himmeli.edges Man page
kda2himmeli.exec Man page
kda2himmeli.identify Man page
kda.analyze Man page
kda.analyze.exec Man page
kda.analyze.simulate Man page
kda.analyze.test Man page
kda.configure Man page
kda.finish Man page
kda.finish.estimate Man page Man page
kda.finish.summarize Man page
kda.finish.trim Man page
kda.prepare Man page
kda.prepare.overlap Man page
kda.prepare.screen Man page
kda.start Man page
kda.start.edges Man page
kda.start.identify Man page
kda.start.modules Man page
Mergeomics Man page
Mergeomics-package Man page
MSEA.KDA.onestep Man page
ssea2kda Man page
ssea2kda.analyze Man page
ssea2kda.import Man page
ssea.analyze Man page
ssea.analyze.observe Man page
ssea.analyze.randgenes Man page
ssea.analyze.randloci Man page
ssea.analyze.simulate Man page
ssea.analyze.statistic Man page
ssea.control Man page
ssea.finish Man page
ssea.finish.details Man page
ssea.finish.fdr Man page
ssea.finish.genes Man page
ssea.meta Man page
ssea.prepare Man page
ssea.prepare.counts Man page
ssea.prepare.structure Man page
ssea.start Man page
ssea.start.configure Man page
ssea.start.identify Man page
ssea.start.relabel Man page
tool.aggregate Man page
tool.cluster Man page
tool.cluster.static Man page
tool.coalesce Man page
tool.coalesce.exec Man page
tool.coalesce.find Man page
tool.coalesce.merge Man page
tool.fdr Man page Man page
tool.fdr.empirical Man page
tool.graph Man page Man page
tool.graph.list Man page
tool.metap Man page
tool.normalize Man page
tool.normalize.quality Man page
tool.overlap Man page Man page Man page
tool.subgraph Man page
tool.subgraph.find Man page Man page
tool.subgraph.stats Man page
tool.translate Man page
tool.unify Man page


R/cle.LS.R R/msea.kda.onestep.R
inst/unitTests/test_kda.analyze.R inst/unitTests/test_ssea.analyze.R
man/MSEA.KDA.onestep.Rd man/Mergeomics-package.Rd man/job.kda.Rd man/kda.analyze.Rd man/kda.analyze.exec.Rd man/kda.analyze.simulate.Rd man/kda.analyze.test.Rd man/kda.configure.Rd man/kda.finish.Rd man/kda.finish.estimate.Rd man/ man/kda.finish.summarize.Rd man/kda.finish.trim.Rd man/kda.prepare.Rd man/kda.prepare.overlap.Rd man/kda.prepare.screen.Rd man/kda.start.Rd man/kda.start.edges.Rd man/kda.start.identify.Rd man/kda.start.modules.Rd man/kda2cytoscape.Rd man/kda2cytoscape.colorize.Rd man/kda2cytoscape.colormap.Rd man/kda2cytoscape.drivers.Rd man/kda2cytoscape.edges.Rd man/kda2cytoscape.exec.Rd man/kda2cytoscape.identify.Rd man/kda2himmeli.Rd man/kda2himmeli.colorize.Rd man/kda2himmeli.colormap.Rd man/kda2himmeli.drivers.Rd man/kda2himmeli.edges.Rd man/kda2himmeli.exec.Rd man/kda2himmeli.identify.Rd man/ssea.analyze.Rd man/ssea.analyze.observe.Rd man/ssea.analyze.randgenes.Rd man/ssea.analyze.randloci.Rd man/ssea.analyze.simulate.Rd man/ssea.analyze.statistic.Rd man/ssea.control.Rd man/ssea.finish.Rd man/ssea.finish.details.Rd man/ssea.finish.fdr.Rd man/ssea.finish.genes.Rd man/ssea.meta.Rd man/ssea.prepare.Rd man/ssea.prepare.counts.Rd man/ssea.prepare.structure.Rd man/ssea.start.Rd man/ssea.start.configure.Rd man/ssea.start.identify.Rd man/ssea.start.relabel.Rd man/ssea2kda.Rd man/ssea2kda.analyze.Rd man/ssea2kda.import.Rd man/tool.aggregate.Rd man/tool.cluster.Rd man/tool.cluster.static.Rd man/tool.coalesce.Rd man/tool.coalesce.exec.Rd man/tool.coalesce.find.Rd man/tool.coalesce.merge.Rd man/tool.fdr.Rd man/ man/tool.fdr.empirical.Rd man/tool.graph.Rd man/ man/tool.graph.list.Rd man/tool.metap.Rd man/tool.normalize.Rd man/tool.normalize.quality.Rd man/tool.overlap.Rd man/ man/ man/tool.subgraph.Rd man/tool.subgraph.find.Rd man/ man/tool.subgraph.stats.Rd man/tool.translate.Rd man/tool.unify.Rd

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