nem {nem} | R Documentation |
The main function to infer a phenotypic hierarchy from data
nem(D,inference="nem.greedy",models=NULL,type="mLL",para=NULL,hyperpara=NULL,Pe=NULL,Pm=NULL,Pmlocal=NULL,local.prior.size=length(unique(colnames(D))),local.prior.bias=1,triples.thrsh=0.5,lambda=0,selEGenes=FALSE,verbose=TRUE)
D |
data matrix with experiments in the columns (binary or continious) |
inference |
search to use exhaustive enumeration; or triples for triple-based inference; or pairwise for the pairwise heuristic; or ModuleNetwork for the module based inference |
models |
a list of adjacency matrices for model search. If NULL, enumerate.models is used for exhaustive enumeration of all possible models. |
type |
mLL or FULLmLL or CONTmLL or CONTmLLDens or CONTmLLRatio |
para |
vector of length two: false positive rate and false negative rate for non-binary data. Used by mLL() |
hyperpara |
vector of length four: used by FULLmLL() for binary data |
Pe |
prior of effect reporter positions in the phenotypic hierarchy (same dimension as D) |
Pm |
prior over models (n x n matrix) |
Pmlocal |
local model prior for pairwise and triple learning. For pairwise learning generated by local.model.prior() according to arguments local.prior.size and local.prior.bias |
local.prior.size |
prior expected number of edges in the graph (for pairwise learning) |
local.prior.bias |
bias towards double-headed edges. Default: 1 (no bias; for pairwise learning) |
triples.thrsh |
threshold for model averaging to combine triple models for each edge |
lambda |
regularization parameter to incorporate prior assumptions. Default: 0 (no regularization) |
selEGenes |
optimize selection of E-genes for each model |
verbose |
do you want to see progression statements" Default: TRUE |
nem
is an interface to the functions score()
, pairwise.posterior()
, triple.posterior
, moduleNetwork
, nem.greedy
.
plot.nem
plots the inferred phenotypic hierarchy as a directed graph, the likelihood distribution of the models (only for exhaustive search) or the posterior position of the effected genes.
An object of class 'score' or 'pairwise' or 'triples' or 'ModuleNetwork' containing slots
graph |
the inferred phenotypic hierarchy |
pos |
posterior distribution of positions of effect reporters |
mappos |
estimated position of effects in the phenotypic hierarchy |
type |
see above |
para |
see above |
hyperpara |
see above |
lambda |
see above |
and additional ones according to the function used for inference.
Florian Markowetz <URL: http://genomics.princeton.edu/~florian>
score
, moduleNetwork
, nem.greedy
, triples.posterior
, pairwise.posterior
, local.model.prior
, enumerate.models
, plot.nem
data("BoutrosRNAi2002") D <- BoutrosRNAiDiscrete[,9:16] p <- c(.13,.05) res1 <- nem(D,para=p,inference="search") res2 <- nem(D,para=p,inference="pairwise") res3 <- nem(D,para=p,inference="triples") res4 <- nem(D,para=p,inference="ModuleNetwork") res5 <- nem(D,para=p,inference="nem.greedy") par(mfrow=c(1,4)) plot(res1,main="exhaustive search") plot(res2,main="pairs") plot(res3,main="triples") plot(res4,main="module network") plot(res5,main="greedy hillclimber")