cpd.accs: Mapping data between compound or gene IDs and KEGG accessions

In DGendooLab/pathviewM: a tool set for pathway based data integration and visualization

Description

Mapping data between compound or gene IDs and KEGG accessions

Usage

data(cpd.accs)
data(cpd.names)
data(kegg.met)
data(ko.ids)
data(rn.list)
data(gene.idtype.list)
data(gene.idtype.bods)
data(cpd.simtypes)

Format

cpd.accs is a data frame with 30054 observations on the following 4 variables. cpd.names is a data frame with 12314 observations on the following 5 variables. kegg.met is a character matrix of 694 rows and 3 columns. ko.ids is a character vector 8511 KEGG ortholog gene IDs, as used in KEGG ortholog pathways. rn.list is a namedlist of 21 vectors. Each vector records the row numbers for one of 21 dfferent compound ID types in cpd.accs data.frame. gene.idtype.list is a character vector of 13 common gene, transcript or protein ID types. Note some ID types are species specific, for example TAIR or ORF. gene.idtype.bods is a list of character vectors ofcommon gene, transcript or protein ID types for the 19 major research species in bods. Each element corresponds to a species. cpd.simtypes is a character vector of 7 common compound related ID types, each of them has over 1000 unique entries. Hence these ID types are good for generating simulation compound data.

Source

ftp://ftp.ebi.ac.uk/pub/databases/chebi/Flat_file_tab_delimited/

http://www.genome.jp/kegg-bin/get_htext?br08001.keg

Examples

data(cpd.accs)
data(rn.list)
names(rn.list)
cpd.accs[rn.list[[1]][1:4],]
lapply(rn.list[1:4], function(rn) cpd.accs[rn[1:4],])

data(kegg.met)
head(kegg.met)

DGendooLab/pathviewM documentation built on Dec. 17, 2021, 4 p.m.