nem {nem}R Documentation

Nested Effects Models - main function

Description

The main function to infer a phenotypic hierarchy from data

Usage

nem(D,inference="pairwise",models=NULL,type="mLL",para=NULL,hyperpara=NULL,Pe=NULL,Pm=NULL,local.prior.size=length(unique(colnames(D))),local.prior.bias=1,verbose=TRUE)

Arguments

D binary data matrix with experiments in the columns
inference search by function score(); or pairwise to use function pairwise.posterior()
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
para vector of length two: false positive rate and false negative rate. Used by mLL()
hyperpara vector of length four: used by FULLmLL()
Pe prior of effect reporter positions in the phenotypic hierarchy
Pm prior over models. 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
local.prior.bias bias towards double-headed edges. Default: 1 (no bias)
verbose do you want to see progression statements" Default: TRUE

Details

nem is an interface to the functions score() and pairwise.posterior().

plot.nem plots the inferred phenotypic hierarchy as a directed graph, and print.nem gives an overview over the 'nem' object.

Value

An object of class 'score' or class 'pairwise' containing slots

graph the inferred phenotypic hierarchy
pos posterior distribution of positions of effect reporters
mappos estimated position of effects in the phenotypic hierarchy

and additional ones according to the function used for inference.

Author(s)

Florian Markowetz <URL: http://genomics.princeton.edu/~florian>

See Also

score, pairwise.posterior, local.model.prior, enumerate.models

Examples

   data("BoutrosRNAi2002")
   D <- BoutrosRNAiDiscrete[,9:16]
   res1 <- nem(D,para=c(.13,.05),inference="search")
   res2 <- nem(D,para=c(.13,.05),inference="pairwise")

   par(mfrow=c(1,2))
   plot(res1,main="by exhaustive search")
   plot(res2,main="by pairwise heuristic")
   

[Package nem version 1.2.0 Index]