a Graph database and R package for omic data integration
Version: 2.8 (13 October 2016)
Grinn is a bioinformatics platform contains an internal graph database (Neo4j), and the R package for -omic studies. Grinn databases incorporate data from several databases including KEGG, SMPDB, HMDB, REACTOME, CheBI, UniProt and ENSEMBL. The R package allows reconstruction of different network types e.g. metabolite-protein-gene, metabolite-protein, metabolite-pathway, protein-gene, protein-pathway and gene-pathway. Grinn applies different correlation-based network analyses to estimate relationships among different omics levels independently from domain knowledge, and with the internal graph database it provides rapid integration of domain knowledge i.e. to aid annotation of unknown metabolites.
#Install devtools R package, if not exist
install.packages("devtools")
#Install grinn package
library(devtools)
devtools::install_github("kwanjeeraw/grinn")
library(grinn)
The internal graph database is a part of the Grinn software to compute the networks. Graph databases are available for Human, Arabidopsis, Mouse, Rat, Saccharomyces cerevisiae and Escherichia coli k-12. The human database is provided by default and can be accessed directly after package installation.
Alternatively the graph databases can be installed locally. The graph databases are available on request.
Local database installation 1. Require Neo4j-community 2.2.0 to 2.3.0 for the internal graph database
- Download and then unzip [Neo4j server](http://neo4j.com/download/)
- Extract and move the graph database files to the Neo4j server directory
- Start the Neo4j server,
for windows: Double-click on %NEO4J_HOME%\bin\Neo4j.bat
for linux: ./bin/neo4j start
for more details see [here](http://neo4j.com/docs/stable/server-installation.html)
#Change the internal database by providing the database url, e.g. "http://database.location:7474/db/data/"
setGrinnDb("http://localhost:7474/db/data/")
#Check current internal database location
getGrinnDb()
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GNU General Public License (v3)
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