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.

Install the latest version of this package by entering the following in R:
AuthorHolger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth
Bioconductor views Bioinformatics GraphsAndNetworks Microarray NetworkInference Pathways SystemsBiology
Date of publicationNone
MaintainerHolger Froehlich <>
LicenseGPL (>= 2)

View on Bioconductor

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


BFSlevel Man page
BoutrosRNAi2002 Man page
BoutrosRNAiDens Man page
BoutrosRNAiDiscrete Man page
BoutrosRNAiExpression Man page
BoutrosRNAiLods Man page
BoutrosRNAiLogFC Man page
bum.dalt Man page
bum.EM Man page
bum.histogram Man page
bum.mle Man page
bum.negLogLik Man page
bum.palt Man page
bum.qalt Man page
bum.ralt Man page
CheckEdge Man page
closest.transitive.greedy Man page
connectModules Man page
createBN Man page
dat Man page
data.likelihood Man page
dat.normalized Man page
dat.unnormalized Man page
dbum Man page
distdecrease Man page
distincrease Man page
distincrease1 Man page
distsame Man page
EdgeEk Man page
effect.likelihood Man page
encode.interventions Man page
enumerate.models Man page
enumerate.models2 Man page
erase.cycles Man page
exhaustive_BN Man page
filterEGenes Man page
fit.BN Man page
fitBUM Man page
FourNeighborhood Man page
FULLmLL Man page
getComponent Man page
getDensityMatrix Man page
getRelevantEGenes Man page
graychange Man page
infer.edge.type Man page
ingreed_BN Man page
internal Man page
inv.logit Man page
is.dag Man page
is.transitive Man page
Ivanova2006RNAiTimeSeries Man page
learn Man page
learn.conditionals Man page
local.model.prior Man page
logit Man page
map.int2node Man page
mLL Man page
moduleNetwork Man page
moduleNetwork.aux Man page
nem Man page
nem.BN Man page
nem.bootstrap Man page
nem.calcSignificance Man page
nem.consensus Man page
nem.cont.preprocess Man page
nem.discretize Man page
nem.featureselection Man page
nem.greedy Man page
nem.greedyMAP Man page
nem.jackknife Man page
nemModelSelection Man page
network.AIC Man page
NiederbergerMediator2012 Man page
NiederbergerMediatorLods Man page
NiederbergerMediatorLogFC Man page
NiederbergerMediatorPVals Man page
OneNeighborhood Man page
optimizecoregraph Man page
optimizemarginal Man page
optimizemarginal.nuInf Man page
pairwise.posterior Man page
parameters_continuous_Bayesian Man page
parameters_continuous_ML Man page
parameters_discrete_Bayesian Man page
parameters_discrete_ML Man page
pbum Man page
PhiDistr Man page
plot.dynoNEM Man page
plotEffects Man page Man page
plot.ModuleNetwork Man page
plotnem Man page
plot.nem Man page
plot.nem.BN Man page
plot.nem.bootstrap Man page
plot.nem.consensus Man page
plot.nem.greedy Man page
plot.nem.greedyMAP Man page
plot.nem.jackknife Man page
plot.pairwise Man page
plot.score Man page
plot.triples Man page
print.dynoNEM Man page Man page
print.ModuleNetwork Man page
print.nem Man page
print.nem.BN Man page
print.nem.bootstrap Man page
print.nem.consensus Man page
print.nem.greedy Man page
print.nem.greedyMAP Man page
print.nem.jackknife Man page
print.pairwise Man page
print.score Man page
print.triples Man page
prior.EgeneAttach.EB Man page
prune.graph Man page
qbum Man page
qqbum Man page
quicknem Man page
rbum Man page
remTwoEdges Man page
SahinRNAi2008 Man page
sampleData Man page
sampleData.BN Man page
sample.effect.likelihood Man page
sample.likelihood Man page
sampleRndNetwork Man page
SCCgraph Man page
score Man page
score_BN Man page
score_continuous_Bayesian Man page
score_continuous_ML Man page
score_discrete_Bayesian Man page
score_discrete_ML Man page Man page
selectEGenes Man page
set.default.parameters Man page
sim.intervention Man page
sim.interventions Man page
subsets Man page
ThreeNeighborhood Man page
transitive.closure Man page
transitive.projections Man page
transitive.reduction Man page
transSubGr Man page
triples.posterior Man page
TwoNeighborhood Man page
VecToMat Man page Man page


R/BFSlevel.R R/BN.R R/DEPN.R R/EMalgo.r R/FULLBayesPrior.R R/FULLmLL.R R/SCCgraph.R R/additionalFunctions.r R/bum.R R/closest.transitive.greedy.R R/dynoNEM_MCMC.R R/enumerate.models.R R/generateNetwork.R R/getDensityMatrix.R R/infer.edge.type.R R/local.model.prior.R R/mLL.R R/mcmc.r R/moduleNetwork.R R/moduleNetwork.orig.R R/nem.BN.R R/nem.R R/nem.bootstrap.R R/nem.calcSignificance.R R/nem.consensus.R R/nem.cont.preprocess.R R/nem.discretize.R R/nem.featureselection.R R/nem.greedy.R R/nem.greedyMAP.R R/nem.jackknife.R R/nemModelSelection.R R/network.AIC.R R/onestep_mcmc.r R/pairwise.posterior.R R/plot.nem.R R/plotEffects.R R/plotnem.R R/print.nem.R R/prune.graph.R R/quicknem.R R/runMCMC.r R/score.R R/selectEGenes.R R/sim.intervention.R R/subsets.R R/transitive.closure.R R/transitive.projections.R R/transitive.reduction.R R/triples.posterior.R R/updateHidden.r R/zzz.R
man/BFSlevel.Rd man/BoutrosRNAi2002.Rd man/Ivanova2006RNAiTimeSeries.Rd man/NiederbergerMediator2012.Rd man/SCCgraph.Rd man/SahinRNAi2008.Rd man/closest.transitive.greedy.Rd man/enumerate.models.Rd man/generateNetwork.Rd man/getDensityMatrix.Rd man/infer.edge.type.Rd man/internal.Rd man/local.model.prior.Rd man/nem.Rd man/nem.bootstrap.Rd man/nem.calcSignificance.Rd man/nem.consensus.Rd man/nem.cont.preprocess.Rd man/nem.discretize.Rd man/nem.jackknife.Rd man/nemModelSelection.Rd man/network.AIC.Rd man/plot.nem.Rd man/plotEffects.Rd man/prior.EgeneAttach.EB.Rd man/prune.graph.Rd man/quicknem.Rd man/selectEGenes.Rd man/set.default.parameters.Rd man/sim.intervention.Rd man/subsets.Rd man/transitive.closure.Rd man/transitive.projections.Rd man/transitive.reduction.Rd

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