nem: (Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies

The package 'nem' allows to reconstruct features of pathways from the nested structure of perturbation effects. It takes as input (1.) a set of pathway components, which were perturbed, and (2.) phenotypic readout of these perturbations (e.g. gene expression, protein expression). The output is a directed graph representing the phenotypic hierarchy.

AuthorHolger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth
Date of publicationNone
MaintainerHolger Froehlich <frohlich@bit.uni-bonn.de>
LicenseGPL (>= 2)
Version2.48.0
http://www.bioconductor.org

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Man pages

BFSlevel: Build (generalized) hierarchy by Breath-First Search

BoutrosRNAi2002: RNAi data on Drosophila innate immune response

closest.transitive.greedy: Find transitively closed graph most similar to the given one

enumerate.models: Exhaustive enumeration of models

generateNetwork: Random networks and data sampling

getDensityMatrix: Calculate density matrix from raw p-value matrix

infer.edge.type: Infer regulation direction for each edge

internal: internal functions

Ivanova2006RNAiTimeSeries: Perturbation Time Series

local.model.prior: Computes a prior to be used for edge-wise model inference

nem: Nested Effects Models - main function

nem.bootstrap: Bootstrapping for nested effect models

nem.calcSignificance: Statistical significance of network hypotheses

nem.consensus: Statistically stabile nested effects models

nem.cont.preprocess: Calculate classification probabilities of perturbation data...

nem.discretize: Discretize perturbation data according to control experiments

nem.jackknife: Jackknife for nested effect models

nemModelSelection: Model selection for nested effect models

network.AIC: AIC/BIC criterion for network graph

NiederbergerMediator2012: Expression measurements upon perturbation of Mediator...

plotEffects: Plots data according to a phenotypic hierarchy

plot.nem: plot nested effect model

prior.EgeneAttach.EB: Initialize E-gene attachment prior for empirical Bayes

prune.graph: Prunes spurious edges in a phenotypic hierarchy

quicknem: Quick run of Nested Effects Models inference

SahinRNAi2008: Combinatorial Protein Knockdowns in the ERBB Signaling...

SCCgraph: Combines Strongly Connected Components into single nodes

selectEGenes: Automatic selection of most relevant effect reporters

set.default.parameters: Get/set hyperparameters

sim.intervention: Simulate interventions in a Nested Effects Model

subsets: Subsets

transitive.closure: Computes the transitive closure of a directed graph

transitive.projections: Computes the transitive approximation of a directed graph

transitive.reduction: Computes the transitive reduction of a graph

Files in this package

nem/DESCRIPTION
nem/NAMESPACE
nem/R
nem/R/BFSlevel.R nem/R/BN.R nem/R/DEPN.R
nem/R/EMalgo.r
nem/R/FULLBayesPrior.R nem/R/FULLmLL.R nem/R/SCCgraph.R
nem/R/additionalFunctions.r
nem/R/bum.R nem/R/closest.transitive.greedy.R nem/R/dynoNEM_MCMC.R nem/R/enumerate.models.R nem/R/generateNetwork.R nem/R/getDensityMatrix.R nem/R/infer.edge.type.R nem/R/local.model.prior.R nem/R/mLL.R
nem/R/mcmc.r
nem/R/moduleNetwork.R nem/R/moduleNetwork.orig.R nem/R/nem.BN.R nem/R/nem.R nem/R/nem.bootstrap.R nem/R/nem.calcSignificance.R nem/R/nem.consensus.R nem/R/nem.cont.preprocess.R nem/R/nem.discretize.R nem/R/nem.featureselection.R nem/R/nem.greedy.R nem/R/nem.greedyMAP.R nem/R/nem.jackknife.R nem/R/nemModelSelection.R nem/R/network.AIC.R
nem/R/onestep_mcmc.r
nem/R/pairwise.posterior.R nem/R/plot.nem.R nem/R/plotEffects.R nem/R/plotnem.R nem/R/print.nem.R nem/R/prune.graph.R nem/R/quicknem.R
nem/R/runMCMC.r
nem/R/score.R nem/R/selectEGenes.R nem/R/sim.intervention.R nem/R/subsets.R nem/R/transitive.closure.R nem/R/transitive.projections.R nem/R/transitive.reduction.R nem/R/triples.posterior.R
nem/R/updateHidden.r
nem/R/zzz.R
nem/build
nem/build/vignette.rds
nem/data
nem/data/BoutrosRNAi2002.RData
nem/data/Ivanova2006RNAiTimeSeries.RData
nem/data/NiederbergerMediator2012.RData
nem/data/SahinRNAi2008.RData
nem/data/datalist
nem/inst
nem/inst/doc
nem/inst/doc/ModuleNetworks1.png
nem/inst/doc/markowetz-thesis-2006.pdf
nem/inst/doc/nem.R
nem/inst/doc/nem.Rnw
nem/inst/doc/nem.pdf
nem/inst/doc/references.bib
nem/man
nem/man/BFSlevel.Rd nem/man/BoutrosRNAi2002.Rd nem/man/Ivanova2006RNAiTimeSeries.Rd nem/man/NiederbergerMediator2012.Rd nem/man/SCCgraph.Rd nem/man/SahinRNAi2008.Rd nem/man/closest.transitive.greedy.Rd nem/man/enumerate.models.Rd nem/man/generateNetwork.Rd nem/man/getDensityMatrix.Rd nem/man/infer.edge.type.Rd nem/man/internal.Rd nem/man/local.model.prior.Rd nem/man/nem.Rd nem/man/nem.bootstrap.Rd nem/man/nem.calcSignificance.Rd nem/man/nem.consensus.Rd nem/man/nem.cont.preprocess.Rd nem/man/nem.discretize.Rd nem/man/nem.jackknife.Rd nem/man/nemModelSelection.Rd nem/man/network.AIC.Rd nem/man/plot.nem.Rd nem/man/plotEffects.Rd nem/man/prior.EgeneAttach.EB.Rd nem/man/prune.graph.Rd nem/man/quicknem.Rd nem/man/selectEGenes.Rd nem/man/set.default.parameters.Rd nem/man/sim.intervention.Rd nem/man/subsets.Rd nem/man/transitive.closure.Rd nem/man/transitive.projections.Rd nem/man/transitive.reduction.Rd
nem/src
nem/src/MCMC.c
nem/src/netlearn.c
nem/src/netlearn.h
nem/src/wrapper.c
nem/vignettes
nem/vignettes/ModuleNetworks1.png
nem/vignettes/markowetz-thesis-2006.pdf
nem/vignettes/nem.Rnw
nem/vignettes/references.bib

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