BioNet (version 1.32.0)

writeHeinz: Write input files for HEINZ

Description

Function to write the input files with the node and edge scores for HEINZ. These files are used to calculate the maximum scoring subnetwork of the graph. The node scores are matched by their names to the nodes of the network, therefore if nodes.scores are provided as a vector or matrix, the vector has to be named, respectively the matrix has to be provided with rownames. If the network contains more nodes than the score vector, the nodes without a score are scored with the average over all nodes. If the nodes should not be scored and used for the calculation of the maximum scoring subnetwork, draw a subnetwork (subNetwork) first and use this for the argument network. The edge scores can be provided as a vector or matrix as the edge.scores argument. If no scores are provided in the arguments, but the use.node.scores or use.edge.scores argument is set to TRUE, it will be automatically looked for the "score" attribute of the nodes and edges of the network.

Usage

writeHeinz(network, file, node.scores=0, edge.scores=0, use.node.score=FALSE, use.edge.score=FALSE)

Arguments

network

Network from which to calculate the maximum scoring subnetwork.

file

File to write to.

node.scores

Numeric vector or matrix of scores for the nodes of the network. Names of the vector or rownames of the matrix have to correspond to the PPI identifiers of the network. The scores can also be used from the node attribute "score", given one score for each node.

edge.scores

Numeric vector of scores for the edges of the network. Edge scores have to be given in the order of the edges in the network. It is better to append the edge scores as the edge attribute "score" to the network: V(network)\$score and set use.scores to TRUE.

use.node.score

Boolean value, whether to use the node attribute "score" in the network as node scores.

use.edge.score

Boolean value, whether to use the edge attribute "score" in the network as edge scores.

See Also

writeHeinzNodes and writeHeinzEdges

Examples

library(DLBCL)
# use Lymphoma data and graph to find module
data(interactome)
data(dataLym)
# get induced subnetwork for all genes contained on the chip
chipGraph <- subNetwork(dataLym$label, interactome)
score <- dataLym$score001
names(score) <- dataLym$label
## Not run: writeHeinz(network=chipGraph, file="lymphoma_001", node.scores=score, edge.scores=0)