kegg.gsets: Generate up-to-date KEGG pathway gene sets
In gage: Generally Applicable Gene-set Enrichment for Pathway Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Generate up-to-date KEGG pathway gene sets for any specified KEGG species.

1	kegg.gsets(species = "hsa", id.type = "kegg", check.new=FALSE)

`species`	character, either the kegg code, scientific name or the common name of the target species. This applies to both pathway and gene.data or cpd.data. When KEGG ortholog pathway is considered, species="ko". Default species="hsa", it is equivalent to use either "Homo sapiens" (scientific name) or "human" (common name).
`id.type`	character, desired ID type for the get sets, case insensitive. Default idtype="kegg", i.e. the primary KEGG gene ID. The other valid option is "entrez", i.e. Entrez Gene. Entrez Gene is the primary KEGG gene ID for many common model organisms, like human, mouse, rat etc, hence these two options have the same effect. For other species, primary KEGG gene ID is not Entrez Gene.
`check.new`	logical, whether to check for any newly added reference pathways online. Default to FALSE. Because such online checking takes time and new reference pathways are rarely added, it is usually not suggested to set this argument TRUE, unless this is really needed.

The latest KEGG pathway gene sets are derived by connecting to the database in real time. This way, we can create high quality gene set data for pathway analysis for over 2400 KEGG species.

Note that we have generated GO gene set for 4 species, human, mouse, rat, yeast as well as KEGG Ortholog, and provided the data in package gageData.

A named list with the following elements:

`kg.sets`	KEGG gene sets, a named list. Each element is a character vector of member gene IDs for a single KEGG pathway. The number of elements of this list is the total number of KEGG pathways defined for the specified species.
`sigmet.idx`	integer indice, which elements in kg.sets are signaling or metabolism pathways.
`sig.idx`	integer indice, which elements in kg.sets are signaling pathways.
`met.idx`	integer indice, which elements in kg.sets are metabolism pathways.
`dise.idx`	integer indice, which elements in kg.sets are disease pathways.

The *.idx elements here are all used to subset kg.sets for more specific type pathway aanlysis.

Weijun Luo <luo_weijun@yahoo.com>

Luo, W., Friedman, M., Shedden K., Hankenson, K. and Woolf, P GAGE: Generally Applicable Gene Set Enrichment for Pathways Analysis. BMC Bioinformatics 2009, 10:161

kegg.gs for precompiled KEGG and other common gene set data collection

#GAGE analysis use the latest KEGG pathway  definitions, instead of
#kegg.gs
kg.hsa=kegg.gsets()
data(gse16873)
hn=(1:6)*2-1
dcis=(1:6)*2
kegg.sigmet=kg.hsa$kg.sets[kg.hsa$sigmet.idx]
gse16873.kegg.p <- gage(gse16873, gsets = kegg.sigmet,
                        ref = hn, samp = dcis)

#E coli KEGG Id is different from Entre Gene
kg.eco=kegg.gsets("eco")
kg.eco.eg=kegg.gsets("eco", id.type="entrez")
head(kg.eco$kg.sets,2)
head(kg.eco.eg$kg.sets,2)