Package: Mergeomics 1.41.0

Zeyneb Kurt

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).

Authors:Ville-Petteri Makinen, Le Shu, Yuqi Zhao, Zeyneb Kurt, Bin Zhang, Xia Yang

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Mergeomics/json (API)

# Install 'Mergeomics' in R:

install.packages('Mergeomics', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

job.kda - Key Driver Analyzing results

On BioConductor:Mergeomics-1.41.0(bioc 3.24)Mergeomics-1.40.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

software

4.45 score 14 scripts 447 downloads 13 mentions 79 exports 0 dependencies

Last updated from:9113a2ad4b. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	139
linux-devel-x86_64	NOTE	369
source / vignettes	OK	421
linux-release-x86_64	NOTE	390
macos-release-arm64	NOTE	245
macos-oldrel-arm64	NOTE	308
windows-devel	NOTE	465
windows-release	NOTE	351
windows-oldrel	NOTE	476
wasm-release	OK	80

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

Dependencies:

Mergeomics

Introduction | Tutorials | Citation | References

Rendered fromMergeomics.Rnwusingutils::Sweave

Last update: 2018-08-30
Started: 2016-02-12

Citation

Development and contributors

Readme and manuals

Help Manual

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