clustNEM: Cluster NEM.

In mnem: Mixture Nested Effects Models

Description

This function clusters the data and performs standard nem on each cluster.

Usage

clustNEM(
  data,
  k = 2:10,
  cluster = NULL,
  starts = 1,
  logtype = 2,
  nem = TRUE,
  getprobspars = list(),
  getaffinitypars = list(),
  Rho = NULL,
  ...
)

Arguments

data	data of log ratios with cells in columns and features in rows
k	number of clusters to check
cluster	given clustering has to correspond to the columns of data
starts	number of random starts for the kmeans algorithm
logtype	logarithm type of the data
nem	if FALSE only clusters the data
getprobspars	list of parameters for the getProbs function
getaffinitypars	list of parameters for the getAffinity function
Rho	perturbation matrix with dimensions nxl with n S-genes and l samples; either as probabilities with the sum of probabilities for a sample less or equal to 1 or discrete with 1s and 0s
...	additional arguments for standard nem function

Value

family of nems; the first k list entries hold full information of the standard nem search

comp	list of all adjacency matrices phi
mw	vector of mixture weights
probs	fake cell probabilities (see mw: mixture weights)

Author(s)

Martin Pirkl

Examples

sim <- simData(Sgenes = 3, Egenes = 2, Nems = 2, mw = c(0.4,0.6))
data <- (sim$data - 0.5)/0.5
data <- data + rnorm(length(data), 0, 1)
resulst <- clustNEM(data, k = 2:3)

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