NetPathMiner (version 1.8.0)

biopax2igraph: Processes BioPAX objects into igraph objects

Description

This function takes BioPAX objects (level 2 or 3) as input, and returns either a metabolic or a signaling network as output.

Usage

biopax2igraph(biopax, parse.as = c("metabolic", "signaling"), expand.complexes = FALSE, inc.sm.molecules = FALSE, verbose = TRUE)

Arguments

biopax

BioPAX object generated by readBiopax.

parse.as

Whether to process file into a metabolic or a signaling network.

expand.complexes

Split protein complexes into individual gene nodes. Ignored if parse.as="metabolic".

inc.sm.molecules

Include small molecules that are participating in signaling events. Ignored if parse.as="metabolic".

verbose

Whether to display the progress of the function.

Value

An igraph object, representing a metbolic or a signaling network.

Details

This function requires rBiopaxParser installed.

Users can specify whether files are processes as metabolic or signaling networks.

Metabolic networks are given as bipartite graphs, where metabolites and reactions represent vertex types. Reactions are constructed from Conversion classes, connecting them to their corresponding Lefts and Rights. Each reaction vertex has genes attribute, listing all Catalysis relationships of this reaction. As a general rule, reactions inherit all annotation attributes of its catalyzig genes.

Signaling network have genes as vertices and edges represent interactions, such as activiation / inhibition. Genes participating in successive reactions are also connected. Signaling interactions are constructed from Control classes, where edges are drawn from controller to controlled.

All annotation attributes are exracted from XRefs associated with the vertices, and are stored according to MIRIAM guidelines (miraim.db, where db is the database name).

See Also

Other Database extraction methods: KGML2igraph; SBML2igraph

Examples

if(require(rBiopaxParser)){
    data(ex_biopax)
    # Process biopax as a metabolic network
    g <- biopax2igraph(ex_biopax)
    plotNetwork(g)

    # Process SBML file as a signaling network
    g <- biopax2igraph(ex_biopax, parse.as="signaling", expand.complexes=TRUE)
}