# Nested Effects Models to reconstruct phenotypic hierarchies

## Documentation for package ‘nem’ version 2.18.0

- DESCRIPTION file.
- Overview of user guides and package vignettes; browse directory.

## Help Pages

B C D E F G I L M N O P Q R S T V W

## -- B --

BFSlevel | Build (generalized) hierarchy by Breath-First Search
BoutrosRNAi2002 | RNAi data on Drosophila innate immune response
BoutrosRNAiDens | RNAi data on Drosophila innate immune response
BoutrosRNAiDiscrete | RNAi data on Drosophila innate immune response
BoutrosRNAiExpression | RNAi data on Drosophila innate immune response
BoutrosRNAiLods | RNAi data on Drosophila innate immune response
BoutrosRNAiLogFC | RNAi data on Drosophila innate immune response
bum.dalt | internal functions
bum.EM | internal functions
bum.histogram | internal functions
bum.mle | internal functions
bum.negLogLik | internal functions
bum.palt | internal functions
bum.qalt | internal functions
bum.ralt | internal functions

## -- C --

CheckEdge | Computes the transitive approximation of a directed graph
closest.transitive.greedy | Find transitively closed graph most similar to the given one
connectModules | internal functions
createBN | internal functions

## -- D --

dat.normalized | Combinatorial Protein Knockdowns in the ERBB Signaling Pathway
dat.unnormalized | Combinatorial Protein Knockdowns in the ERBB Signaling Pathway
data.likelihood | internal functions
dbum | internal functions
distdecrease | Computes the transitive approximation of a directed graph
distincrease | Computes the transitive approximation of a directed graph
distincrease1 | Computes the transitive approximation of a directed graph
distsame | Computes the transitive approximation of a directed graph

## -- E --

EdgeEk | Computes the transitive approximation of a directed graph
effect.likelihood | internal functions
encode.interventions | internal functions
enumerate.models | Exhaustive enumeration of models
enumerate.models2 | internal functions
erase.cycles | internal functions
exhaustive_BN | internal functions

## -- F --

filterEGenes | Automatic selection of most relevant effect reporters
fit.BN | internal functions
fitBUM | internal functions
FourNeighborhood | Computes the transitive approximation of a directed graph
FULLmLL | internal functions

## -- G --

getComponent | internal functions
getDensityMatrix | Calculate density matrix from raw p-value matrix
getRelevantEGenes | Automatic selection of most relevant effect reporters
graychange | internal functions

## -- I --

infer.edge.type | Infer regulation direction for each edge
ingreed_BN | internal functions
internal | internal functions
inv.logit | internal functions
is.dag | internal functions
is.transitive | Computes the transitive approximation of a directed graph

## -- L --

learn | internal functions
learn.conditionals | internal functions
local.model.prior | Computes a prior to be used for edge-wise model inference
logit | internal functions

## -- M --

map.int2node | Combinatorial Protein Knockdowns in the ERBB Signaling Pathway
mLL | internal functions
moduleNetwork | internal functions
moduleNetwork.aux | internal functions

## -- N --

nem | Nested Effects Models - main function
nem.BN | internal functions
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 according to control experiments
nem.discretize | Discretize perturbation data according to control experiments
nem.featureselection | internal functions
nem.greedy | internal functions
nem.greedyMAP | internal functions
nem.jackknife | Jackknife for nested effect models
nemModelSelection | Model selection for nested effect models
network.AIC | AIC/BIC criterion for network graph

## -- O --

OneNeighborhood | Computes the transitive approximation of a directed graph
optimizecoregraph | internal functions
optimizemarginal | internal functions
optimizemarginal.nuInf | internal functions

## -- P --

pairwise.posterior | internal functions
parameters_continuous_Bayesian | internal functions
parameters_continuous_ML | internal functions
parameters_discrete_Bayesian | internal functions
parameters_discrete_ML | internal functions
pbum | internal functions
PhiDistr | internal functions
plot.ModuleNetwork | plot nested effect model
plot.nem | plot nested effect model
plot.nem.BN | plot nested effect model
plot.nem.bootstrap | plot nested effect model
plot.nem.consensus | plot nested effect model
plot.nem.greedy | plot nested effect model
plot.nem.greedyMAP | plot nested effect model
plot.nem.jackknife | plot nested effect model
plot.pairwise | plot nested effect model
plot.score | plot nested effect model
plot.triples | plot nested effect model
plotEffects | Plots data according to a phenotypic hierarchy
plotnem | plot nested effect model
print.ModuleNetwork | Nested Effects Models - main function
print.nem | Nested Effects Models - main function
print.nem.BN | Nested Effects Models - main function
print.nem.bootstrap | Bootstrapping for nested effect models
print.nem.consensus | Statistically stabile nested effects models
print.nem.greedy | Nested Effects Models - main function
print.nem.greedyMAP | Nested Effects Models - main function
print.nem.jackknife | Jackknife for nested effect models
print.pairwise | Nested Effects Models - main function
print.score | Nested Effects Models - main function
print.triples | Nested Effects Models - main function
prune.graph | Prunes spurious edges in a phenotypic hierarchy

## -- Q --

qbum | internal functions
qqbum | internal functions
quicknem | Quick run of Nested Effects Models inference

## -- R --

rbum | internal functions
remTwoEdges | Computes the transitive approximation of a directed graph

## -- S --

SahinRNAi2008 | Combinatorial Protein Knockdowns in the ERBB Signaling Pathway
sample.effect.likelihood | internal functions
sample.likelihood | internal functions
sampleData | Random networks and data sampling
sampleData.BN | Random networks and data sampling
sampleRndNetwork | Random networks and data sampling
SCCgraph | Combines Strongly Connected Components into single nodes
score | internal functions
score.network | internal functions
score_BN | internal functions
score_continuous_Bayesian | internal functions
score_continuous_ML | internal functions
score_discrete_Bayesian | internal functions
score_discrete_ML | internal functions
selectEGenes | Automatic selection of most relevant effect reporters
set.default.parameters | Get/set hyperparameters
sim.intervention | Simulate interventions in a Nested Effects Model
sim.interventions | internal functions
subsets | Subsets

## -- T --

ThreeNeighborhood | Computes the transitive approximation of a directed graph
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
transSubGr | Computes the transitive approximation of a directed graph
triples.posterior | internal functions
TwoNeighborhood | Computes the transitive approximation of a directed graph

## -- V --

VecToMat | Computes the transitive approximation of a directed graph

## -- W --

which.is.max | internal functions