nem.greedy {nem} | R Documentation |
Infers a phenotypic hierarchy using a greedy search strategy
Description
Starting from an initial graph (default: no edges), this strategy successively adds those edges, which most inrease the likelihood of the data under the model.
Usage
nem.greedy(D,initial=NULL,type="mLL",Pe=NULL,Pm=NULL,lambda=0,delta=1,para=NULL,hyperpara=NULL,verbose=TRUE)
## S3 method for class 'nem.greedy':
print(x, ...)
Arguments
D |
data matrix. Columns correspond to the nodes in the silencing scheme. Rows are phenotypes. |
initial |
initial model to start greedy hillclimbing from (default: no edges) |
type |
(1.) marginal likelihood "mLL" (only for cout matrix D), or (2.) full marginal likelihood "FULLmLL" integrated over a and b and depending on hyperparameters a0, a1, b0, b1 (only for count matrix D), or (3.) "CONTmLL" marginal likelihood for probability matrices, or (4.) "CONTmLLDens" marginal likelihood for probability log-density matrices, or (5.) "CONTmLLRatio" for log-odds ratio matrices |
Pe |
prior position of effect reporters. Default: uniform over nodes in hierarchy |
Pm |
prior on model graph (n x n matrix) with entries 0 <= priorPhi[i,j] <= 1 describing the probability of an edge between gene i and gene j. |
lambda |
regularization parameter to incorporate prior assumptions. |
delta |
regularization parameter for automated E-gene subset selection (CONTmLLRatio only) |
para |
vector with parameters a and b for "mLL", if count matrices are used |
hyperpara |
vector with hyperparameters a0, b0, a1, b1 for "FULLmLL" |
verbose |
do you want to see progress statements printed or not? Default: TRUE |
x |
nem object |
... |
other arguments to pass |
Value
graph |
the inferred directed graph (graphNEL object) |
mLL |
marginal likelihood of final model |
pos |
posterior over effect positions |
mappos |
MAP estimate of effect positions |
type |
as used in function call |
para |
as used in function call |
hyperpara |
as used in function call |
lambda |
as in function call |
selected |
selected E-gene subset |
Author(s)
Holger Froehlich
See Also
nem
Examples
# Drosophila RNAi and Microarray Data from Boutros et al, 2002
data("BoutrosRNAi2002")
D <- BoutrosRNAiDiscrete[,9:16]
nem.greedy(D, para=c(.13,.05))
[Package
nem version 2.4.0
Index]