To perform network-based enrichment analysis a gene regulatory network (GRN) is required. There are well-studied processes and organisms for which comprehensive and well-annotated regulatory networks are available, e.g. the RegulonDB for E. coli and Yeastract for S. cerevisiae. However, in many cases such a network is missing. A first simple workaround is to compile a network from regulations in pathway databases such as KEGG.
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An organism in KEGG three letter code, e.g. ‘hsa’ for
‘Homo sapiens’. Alternatively, and mainly for backward
compatibility, this can also be either a list of
Pathway database. This should be one or more DBs out of 'kegg',
'reactome', 'biocarta', and 'nci'. See
Should gene regulatory interactions be classified as
activating (+) or inhibiting (-)? If TRUE, this will drop interactions for
which such a classification cannot be made (e.g. binding events).
Otherwise, all interactions found in the pathway DB will be included.
Should gene identifiers be mapped to NCBI Entrez Gene IDs?
This only applies to Reactome and NCI as they both use UNIPROT IDs. This is
typically recommended when using the GRN for network-based enrichment
analysis with the EnrichmentBrowser. Default is
Should the original interaction type descriptions be kept?
If TRUE, this will keep the long description of interaction types as found
in the original KGML and BioPax pathway files. Default is
For KEGG: should the GRN be compiled from the native KGML
files or should graphite's pathway topology conversion be used? See the
vignette of the graphite package for details. This is mostly for backward
compatibility. Default is
The GRN in plain matrix format. Two columns named
TO (the regulated gene) are guaranteed. Additional
LONG.TYPE, are included if option
keep.type is activated.
Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>
kegg.grn <- compileGRN(org="hsa", db="kegg")
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