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nem (version 2.46.0)

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

Description

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.

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Version

Version

2.46.0

License

GPL (>= 2)

Maintainer

Holger Froehlich

Last Published

February 15th, 2017

Functions in nem (2.46.0)

BoutrosRNAi2002

RNAi data on Drosophila innate immune response
nem.cont.preprocess

Calculate classification probabilities of perturbation data according to control experiments
nem.calcSignificance

Statistical significance of network hypotheses
closest.transitive.greedy

Find transitively closed graph most similar to the given one
enumerate.models

Exhaustive enumeration of models
nem.consensus

Statistically stabile nested effects models
generateNetwork

Random networks and data sampling
BFSlevel

Build (generalized) hierarchy by Breath-First Search
infer.edge.type

Infer regulation direction for each edge
internal

internal functions
nem.jackknife

Jackknife for nested effect models
getDensityMatrix

Calculate density matrix from raw p-value matrix
prior.EgeneAttach.EB

Initialize E-gene attachment prior for empirical Bayes
SCCgraph

Combines Strongly Connected Components into single nodes
transitive.closure

Computes the transitive closure of a directed graph
plotEffects

Plots data according to a phenotypic hierarchy
SahinRNAi2008

Combinatorial Protein Knockdowns in the ERBB Signaling Pathway
Ivanova2006RNAiTimeSeries

Perturbation Time Series
nem.bootstrap

Bootstrapping for nested effect models
nem

Nested Effects Models - main function
NiederbergerMediator2012

Expression measurements upon perturbation of Mediator subunits
subsets

Subsets
getRelevantEGenes

Automatic selection of most relevant effect reporters
network.AIC

AIC/BIC criterion for network graph
sim.intervention

Simulate interventions in a Nested Effects Model
nemModelSelection

Model selection for nested effect models
transitive.projections

Computes the transitive approximation of a directed graph
transitive.reduction

Computes the transitive reduction of a graph
plot.nem

plot nested effect model
local.model.prior

Computes a prior to be used for edge-wise model inference
prune.graph

Prunes spurious edges in a phenotypic hierarchy
quicknem

Quick run of Nested Effects Models inference
nem.discretize

Discretize perturbation data according to control experiments
set.default.parameters

Get/set hyperparameters