MakePredictionsFromCCG: make predictions from CCG

In CausalR: Causal network analysis methods

Description

Create a matrix of predictions for a particular hypothesis starting from a network with separate nodes for up- and down-regulation (+ve and -ve). The output is an array containing the relationship between each node and the hypothesis. The hypothesis provided will be the vertex id of one of the nodes in the network (as an integer or name including + or - for up/down regulation). The signOfHypothesis variable should be a 1 or -1, indicating up/down regulation. (It generally shouldn't be necessary to reverse the sign of a node when working from a CCG, but this facility is included for consistency with MakePredictionsFromCG)

Usage

MakePredictionsFromCCG(hypothesisnode, signOfHypothesis, network, delta,
  nodesInExperimentalData = NULL)

Arguments

hypothesisnode	a hypothesis node
signOfHypothesis	the direction of change of hypothesis node
network	a computational causal graph
delta	the number of edges across which the hypothesis should be followed
nodesInExperimentalData	the number of nodes in experimental data

Value

an matrix containing the relationship between each node and the hypothesis

Examples

network <- system.file(package='CausalR', 'extdata', 'testNetwork.sif')
ccg <- CreateCCG(network)
MakePredictionsFromCCG('NodeA', +1, ccg, 2)

CausalR documentation built on Nov. 8, 2020, 5:25 p.m.