Description Usage Arguments Details Value Author(s) See Also Examples
This function takes BioPAX objects (level 2 or 3) as input, and returns either a metabolic or a signaling network as output.
1 2 | biopax2igraph(biopax, parse.as = c("metabolic", "signaling"),
expand.complexes = FALSE, inc.sm.molecules = FALSE, verbose = TRUE)
|
biopax |
BioPAX object generated by |
parse.as |
Whether to process file into a metabolic or a signaling network. |
expand.complexes |
Split protein complexes into individual gene nodes. Ignored if
|
inc.sm.molecules |
Include small molecules that are participating in signaling events. Ignored if
|
verbose |
Whether to display the progress of the function. |
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).
An igraph object, representing a metbolic or a signaling network.
Ahmed Mohamed
Other Database extraction methods: KGML2igraph,
SBML2igraph
1 2 3 4 5 6 7 8 9 | 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)
}
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