BFSlevel | Build (generalized) hierarchy by Breath-First Search |
BoutrosRNAi2002 | RNAi data on Drosophila innate immune response |
BoutrosRNAiDiscrete | RNAi data on Drosophila innate immune response |
BoutrosRNAiExpression | RNAi data on Drosophila innate immune response |
connectModules | Infers a phenotypic hierarchy using the module network |
enumerate.models | Exhaustive enumeration of models |
FULLmLL | Full marginal likelihood of a phenotypic hierarchy |
local.model.prior | Computes a prior to be used for edge-wise model inference |
mLL | Marginal likelihood of a phenotypic hierarchy |
moduleNetwork | Infers a phenotypic hierarchy using the module network |
nem | Nested Effects Models - main function |
nem.cont.preprocess | Calculate classification probabilities of perturbation data according to control experiments |
nem.discretize | Discretize perturbation data according to control experiments |
nemModelSelection | model selection for nested effect models |
network.AIC | AIC criterion for network graph |
pairwise.posterior | Infers a phenotypic hierarchy edge by edge |
plot.effects | Plots data according to a phenotypic hierarchy |
plot.ModuleNetwork | plot nested effect model |
plot.nem | plot nested effect model |
plot.pairwise | plot nested effect model |
plot.score | plot nested effect model |
plot.triples | plot nested effect model |
print.ModuleNetwork | Infers a phenotypic hierarchy using the module network |
print.pairwise | Infers a phenotypic hierarchy edge by edge |
print.score | Computes the marginal likelihood of phenotypic hierarchies |
print.triples | Infers a phenotypic hierarchy from triples |
SCCgraph | Combines Strongly Connected Components into single nodes |
score | Computes the marginal likelihood of phenotypic hierarchies |
subsets | Subsets |
transitive.closure | Computes the transitive closure of a directed graph |
transitive.reduction | Computes the transitive reduction of a graph |
triples.posterior | Infers a phenotypic hierarchy from triples |