KEGGSearch: Comprehensive KEGG Data Retrieval Using Multiple Sources

Description

The KEGGSearch package provides an extensive toolkit for retrieving KEGG (Kyoto Encyclopedia of Genes and Genomes) information from multiple sources, enabling flexible and comprehensive access to biological pathway and module data. It includes functions to query KEGG IDs via the official KEGG REST API and alternative sources such as Bio2RDF, as well as a manually curated dataset for enhanced coverage of KEGG modules. The package facilitates efficient data extraction and integration for bioinformatics analysis.

Key Functions

• KEGGList() – Retrieves KEGG entity names (pathways, compounds, etc.) using the official KEGG REST API.
• GETKEGGNames() – Fetches KEGG entity names via the Bio2RDF API as an alternative data source.
• GETKEGG_Module() – Combines Bio2RDF data with a manually curated KEGG module table to enhance data availability.

This package is useful for researchers and bioinformaticians needing reliable and extensive access to KEGG resources for biological analysis and pathway enrichment studies.

Installation

You can install the development version of KEGGSearch from GitHub with:

# install.packages("devtools")
devtools::install_github("Gabriele-Conti/KEGGSearch")

Depends: dplyr, tibble, httr, jsonlite

Example

This is a basic example which shows you how to solve a common problem:

# import dependances
library(KEGGPackage)
library(dplyr)
library(tibble)
library(httr)
library(jsonlite)

## KEGGList basic example code
entry <- c("map01100", "map01110", "map01120")
result <- KEGGList(entry = entry, database = "pathway")
#> [1] "Selected param: pathway"
#> Querying: https://rest.kegg.jp/list/pathway
print(result)
#>         V1                                           V2
#> 1 map01100                           Metabolic pathways
#> 2 map01110        Biosynthesis of secondary metabolites
#> 3 map01120 Microbial metabolism in diverse environments

## GETKEGGNames basic example code
KEGG_IDs <- c("map01100", "map01110", "map01120")
result <- GETKEGGNames(KEGG_IDs)
print(result)
#>                                                                   Names
#> map01100                           Metabolic pathways\n [kegg:map01100]
#> map01110        Biosynthesis of secondary metabolites\n [kegg:map01110]
#> map01120 Microbial metabolism in diverse environments\n [kegg:map01120]

## KEGGList basic example code
modules_IDs <- c("M00005", "M00045", "M00060")
result <- GETKEGG_Module(modules_IDs)
#> All KEGG modules are present in the local database ...
print(result)
#>        KEGG.modules
#> M00005       M00005
#> M00045       M00045
#> M00060       M00060
#>                                                                  Description
#> M00005                                  PRPP biosynthesis, ribose 5P => PRPP
#> M00045 Histidine degradation, histidine => N-formiminoglutamate => glutamate
#> M00060              KDO2-lipid A biosynthesis, Raetz pathway, LpxL-LpxM type

Citation

If you use this R package please cite this GitHub in your article:

@Manual{,
  title = {KEGGSearch: Comprehensive KEGG Data Retrieval Using Multiple Sources},
  author = {Gabriele Conti},
  year = {2025},
  note = {R package version 0.0.1},
  url = {https://github.com/Gabriele-Conti/KEGGSearch.git},
}

Example
Conti, G. (2025) KEGGSearch: Comprehensive KEGG Data Retrieval Using Multiple Sources (v0.0.1). Available on Github: https://github.com/Gabriele-Conti/KEGGSearch