title: ADGO: analysis of differentially expressed gene sets using composite GO annotation.
abstract: BACKGROUND
  Genes are typically expressed in modular manners in biological processes. Recent studies reflect such features in analyzing gene expression patterns by directly scoring gene sets. Gene annotations have been used to define the gene sets, which have served to reveal specific biological themes from expression data. However, current annotations have limited analytical power, because they are classified by single categories providing only unary information for the gene sets.
  
  
  RESULTS
  Here we propose a method for discovering composite biological themes from expression data. We intersected two annotated gene sets from different categories of Gene Ontology (GO). We then scored the expression changes of all the single and intersected sets. In this way, we were able to uncover, for example, a gene set with the molecular function F and the cellular component C that showed significant expression change, while the changes in individual gene sets were not significant. We provided an exemplary analysis for HIV-1 immune response. In addition, we tested the method on 20 public datasets where we found many 'filtered' composite terms the number of which reached approximately 34% (a strong criterion, 5% significance) of the number of significant unary terms on average. By using composite annotation, we can derive new and improved information about disease and biological processes from expression data.
  
  
  BACKGROUND
  We provide a web application (ADGO: http://array.kobic.re.kr/ADGO) for the analysis of differentially expressed gene sets with composite GO annotations. The user can analyze Affymetrix and dual channel array (spotted cDNA and spotted oligo microarray) data for four species: human, mouse, rat and yeast.
  
  
  BACKGROUND
  chu@kribb.re.kr
  
  
  BACKGROUND
  http://array.kobic.re.kr/ADGO.
authors.affiliation: Korean BioInformation Center, Korea Research Institute of Bioscience and Biotechnology, 52 Eoun-dong Yuseong-gu, Daejeon 305-333, Korea.
authors.forename: Dougu
authors.initials: D
authors.lastname: Nam
authors.forename: Sang-Bae
authors.initials: SB
authors.lastname: Kim
authors.forename: Seon-Kyu
authors.initials: SK
authors.lastname: Kim
authors.forename: Sungjin
authors.initials: S
authors.lastname: Yang
authors.forename: Seon-Young
authors.initials: SY
authors.lastname: Kim
authors.forename: In-Sun
authors.initials: IS
authors.lastname: Chu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D030562:Databases, Protein; D004282:Documentation / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000378:metabolism*; D012984:Software
chemical_list: D011506:Proteins