NetPathMiner (version 1.8.0)

KGML2igraph: Processes KGML files into igraph objects

Description

This function takes KGML files as input, and returns either a metabolic or a signaling network as output.

Usage

KGML2igraph(filename, parse.as = c("metabolic", "signaling"), expand.complexes = FALSE, verbose = TRUE)

Arguments

filename

A character vector containing the KGML files to be processed. If a directory path is provided, all *.xml files in it and its subdirectories are included.

parse.as

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

expand.complexes

Split protein complexes into individual gene nodes. This argument is 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

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. This is constructed from xml node in KGML file, connecting them to their corresponding substrates and products. Each reaction vertex has genes attribute, listing all genes associated with the 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 parsing method processes , and interactions from KGML files.

To generate a genome scale network, simply provide a list of files to be parsed, or put all file in a directory, as pass the directory path as filename

See Also

Other Database extraction methods: SBML2igraph; biopax2igraph

Examples

if(is.loaded("readkgmlfile")){ # This is false if libxml2 wasn't available at installation.
    filename <- system.file("extdata", "hsa00860.xml", package="NetPathMiner")

    # Process KGML file as a metabolic network
    g <- KGML2igraph(filename)
    plotNetwork(g)

    # Process KGML file as a signaling network
    g <- KGML2igraph(filename, parse.as="signaling", expand.complexes=TRUE)
    plotNetwork(g)
}