title: GARNET--gene set analysis with exploration of annotation relations.
abstract: BACKGROUND
  Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information.
  
  
  RESULTS
  GARNET (Gene Annotation Relationship NEtwork Tools) is an integrative platform for gene set analysis with many novel features. It includes tools for retrieval of genes from annotation database, statistical analysis & visualization of annotation relationships, and managing gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, we have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules--gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations.
  
  
  CONCLUSIONS
  GARNET (gene annotation relationship network tools) is an integrative platform for diverse types of gene set analysis, where complex relationships among gene annotations can be easily explored with an intuitive network visualization tool (http://garnet.isysbio.org/ or http://ercsb.ewha.ac.kr/garnet/).
authors.affiliation: Information Center for Bio-Pharmacological Network, Seoul National University, Suwon 443-270, Korea. krho@i-pharm.org
authors.forename: Kyoohyoung
authors.initials: K
authors.lastname: Rho
authors.forename: Bumjin
authors.initials: B
authors.lastname: Kim
authors.forename: Youngjun
authors.initials: Y
authors.lastname: Jang
authors.forename: Sanghyun
authors.initials: S
authors.lastname: Lee
authors.forename: Taejeong
authors.initials: T
authors.lastname: Bae
authors.forename: Jihae
authors.initials: J
authors.lastname: Seo
authors.forename: Chaehwa
authors.initials: C
authors.lastname: Seo
authors.forename: Jihyun
authors.initials: J
authors.lastname: Lee
authors.forename: Hyunjung
authors.initials: H
authors.lastname: Kang
authors.forename: Ungsik
authors.initials: U
authors.lastname: Yu
authors.forename: Sunghoon
authors.initials: S
authors.lastname: Kim
authors.forename: Sanghyuk
authors.initials: S
authors.lastname: Lee
authors.forename: Wan Kyu
authors.initials: WK
authors.lastname: Kim
mesh_terms: D019295:Computational Biology / Q000379:methods; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D016247:Information Storage and Retrieval / Q000379:methods*; D058977:Molecular Sequence Annotation; D012984:Software