SBML2igraph: Processes SBML files into igraph objects

In aiminy/NetPathMiner: NetPathMiner for Biological Network Construction, Path Mining and Visualization

Description

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

Usage

SBML2igraph(filename, parse.as = c("metabolic", "signaling"),
  miriam.attr = "all", gene.attr, expand.complexes, verbose = TRUE)

Arguments

filename	A character vector containing the SBML files to be processed. If a directory path is provided, all *.xml and *.sbml files in it and its subdirectories are included.
parse.as	Whether to process file into a metabolic or a signaling network.
miriam.attr	A list of annotation attributes to be extracted. If "all", then all attibutes written in MIRIAM guidelines (see Details) are extracted (Default). If "none", then no attributes are extracted. Otherwise, only attributes matching those specified are extracted.
gene.attr	An attribute to distinguish species representing genes from those representing small molecules (see Details). Ignored if parse.as="metabolic".
expand.complexes	Split protein complexes into individual gene nodes. Ignored if parse.as="metabolic", or when gene.attr is not provided.
verbose	Whether to display the progress of the function.

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 ListOfReactions in SBML file, connecting them to their corresponding substrates and products (ListOfSpecies). Each reaction vertex has genes attribute, listing all modifiers 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. Since SBML format may represent singling events as reaction, all species are assumed to be genes (rather than small molecules). For a simple path S0 -> R1 -> S1, in signaling network, the path will be S0 -> M(R1) -> S1 where M(R1) is R1 modifier(s). To ditiguish gene species from small molecules, user can provide gene.attr (for example: miriam.uniprot or miriam.ncbigene) where only annotated species are considered genes.

All annotation attributes written according to MIRIAM guidlines (either urn:miriam:xxx:xxx or http://identifiers.org/xxx/xxx) are etxracted by default. Non-conforming attributes can be extracted by specifying miriam.attr.

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

Note: This function requires libSBML installed (Please see the installation instructions in the Vignette). Some SBML level-3 files may requires additional libraries also (An infomative error will be displayed when parsing such files). Please visit http://sbml.org/Documents/Specifications/SBML_Level_3/Packages for more information.

Value

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

Author(s)

Ahmed Mohamed

See Also

Other Database extraction methods: KGML2igraph, biopax2igraph

Examples

if(is.loaded("readsbmlfile")){ # This is false if libSBML wasn't available at installation.
    filename <- system.file("extdata", "porphyrin.sbml", package="NetPathMiner") 

    # Process SBML file as a metabolic network 
    g <- SBML2igraph(filename)
    plotNetwork(g)

    # Process SBML file as a signaling network
    g <- SBML2igraph(filename, parse.as="signaling", 
                    gene.attr="miriam.uniprot",expand.complexes=TRUE)
    dev.new()
    plotNetwork(g)
}

aiminy/NetPathMiner documentation built on May 12, 2019, 3:38 a.m.