makedata: Generate artificial dataset given a network and list of...

In ddepn: Dynamic Deterministic Effects Propagation Networks: Infer signalling networks for timecourse RPPA data.

Description

Dataset generation using an input network, list of stimuli and various experiment parameters.

Usage

makedata(phi, stimuli, R.t = 3, R.b = 3, TT = 10, mu.bg = 0, sd.bg = 0.1, 
	mu.signal.a = 2, sd.signal.a = 0.5, mu.signal.i = -2, sd.signal.i = 0.5,
	allow.stim.off = FALSE)

Arguments

phi	Adjacency matrix.The input network.
stimuli	List containing all stimuli.
R.t	Integer. Number of technical replicates. So far, no distinction is done between technical and biological replicates, so in total a number of R.t \cdot R.b replicates is generated. If given as vector of length equal to the length of stimuli, then each element denotes the numbers of replicates in each experiment, denoted by the corresponding element in stimuli.
R.b	Integer. Number of biological replicates. So far, no distinction is done between technical and biological replicates, so in total a number of R.t \cdot R.b replicates is generated. Can also be given as vector, with the same effect as for R.t.
TT	Integer.Number of timepoints in the experiment. Analogously to R.t and R.b, can be given as vector, denoting the numbers of time points in each separate experiment.
mu.bg	Double. Mean background intensity (for passive state of the protein.
sd.bg	Double. Sd for background intensity.
mu.signal.a	Double. Mean intensity for activation.
sd.signal.a	Double. Sd for activation intensity.
mu.signal.i	Double. Mean intensity for inhibition.
sd.signal.i	Double. Sd for inhibition intensity.
allow.stim.off	Boolean. If TRUE, a stimulus can become inactive at some time point, if FALSE, the stimulus will be always active.

Details

Generates a dataset from the given network, stimuli and parameters.

Value

A list containing the dataset:

datx	The data matrix.
gammax	Matrix of true state transitions.
stimuli	The list of stimuli.
phi	The network.
R.t	Technical replicates.
R.b	Biological replicates.
TT	Number of timepoints.

Author(s)

Christian Bender

Examples

## Not run: 
library(ddepn)
dataset <- makedata(matrix(sample(c(0,1,2),9,replace=TRUE),nrow=3,
	dimnames=list(LETTERS[1:3],LETTERS[1:3])), list(A=1))

## End(Not run)

ddepn documentation built on May 2, 2019, 4:42 p.m.