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

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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.

Author
Holger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth
Date of publication
None
Maintainer
Holger Froehlich <frohlich@bit.uni-bonn.de>
License
GPL (>= 2)
Version
2.48.0
URLs

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

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