nem: Implementation of the original NEM

In mnem: Mixture Nested Effects Models

Description

Infers a signalling pathway from peerturbation experiments.

Usage

nem(
  D,
  search = "greedy",
  start = NULL,
  method = "llr",
  parallel = NULL,
  reduce = FALSE,
  weights = NULL,
  runs = 1,
  verbose = FALSE,
  redSpace = NULL,
  trans.close = TRUE,
  subtopo = NULL,
  prior = NULL,
  ratio = TRUE,
  domean = TRUE,
  modulesize = 5,
  fpfn = c(0.1, 0.1),
  Rho = NULL,
  logtype = 2,
  modified = FALSE,
  ...
)

Arguments

D	data matrix with observed genes as rows and knock-down experiments as columns
search	either "greedy", "modules" or "exhaustive" (not recommended for more than five S-genes)
start	either NULL ("null") or a specific network to start the greedy
method	"llr" for log odds or p-values densities or "disc" for binary data
parallel	NULL for no parallel optimization or an integer for the number of threads
reduce	reduce search space (TRUE) for exhaustive search
weights	a numeric vector of weights for the columns of D
runs	the number of runs for the greedy search
verbose	for verbose output (TRUE)
redSpace	reduced search space for exhaustive search; see result of exhaustive search with reduce = TRUE
trans.close	if TRUE uses the transitive closure of adj
subtopo	optional matrix with the subtopology theta as adjacency matrix
prior	a prior network matrix for adj
ratio	if FALSE uses alternative distance for the model score
domean	if TRUE summarizes duplicate columns
modulesize	the max number of S-genes included in one module for search = "modules"
fpfn	numeric vector of length two with false positive and false negative rates
Rho	optional perturbation matrix
logtype	log base of the log odds
modified	if TRUE, assumes a prepocessed data matrix
...	optional parameters for future search methods

Value

transitively closed matrix or graphNEL

Author(s)

Martin Pirkl

Examples

D <- matrix(rnorm(100*3), 100, 3)
colnames(D) <- 1:3
rownames(D) <- 1:100
adj <- diag(3)
colnames(adj) <- rownames(adj) <- 1:3
scoreAdj(D, adj)

mnem documentation built on Nov. 18, 2020, 2 a.m.