title: A decision analysis model for KEGG pathway analysis.
abstract: BACKGROUND
  The knowledge base-driven pathway analysis is becoming the first choice for many investigators, in that it not only can reduce the complexity of functional analysis by grouping thousands of genes into just several hundred pathways, but also can increase the explanatory power for the experiment by identifying active pathways in different conditions. However, current approaches are designed to analyze a biological system assuming that each pathway is independent of the other pathways.
  
  
  RESULTS
  A decision analysis model is developed in this article that accounts for dependence among pathways in time-course experiments and multiple treatments experiments. This model introduces a decision coefficient-a designed index, to identify the most relevant pathways in a given experiment by taking into account not only the direct determination factor of each Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway itself, but also the indirect determination factors from its related pathways. Meanwhile, the direct and indirect determination factors of each pathway are employed to demonstrate the regulation mechanisms among KEGG pathways, and the sign of decision coefficient can be used to preliminarily estimate the impact direction of each KEGG pathway. The simulation study of decision analysis demonstrated the application of decision analysis model for KEGG pathway analysis.
  
  
  CONCLUSIONS
  A microarray dataset from bovine mammary tissue over entire lactation cycle was used to further illustrate our strategy. The results showed that the decision analysis model can provide the promising and more biologically meaningful results. Therefore, the decision analysis model is an initial attempt of optimizing pathway analysis methodology.
authors.affiliation: College of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.|College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Junli
authors.initials: J
authors.lastname: Du
authors.affiliation: College of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Manlin
authors.initials: M
authors.lastname: Li
authors.affiliation: College of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Zhifa
authors.initials: Z
authors.lastname: Yuan
authors.affiliation: College of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Mancai
authors.initials: M
authors.lastname: Guo
authors.affiliation: Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
authors.forename: Jiuzhou
authors.initials: J
authors.lastname: Song
authors.affiliation: College of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
authors.forename: Xiaozhen
authors.initials: X
authors.lastname: Xie
authors.affiliation: College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, People's Republic of China. liml75@126.com.
authors.forename: Yulin
authors.initials: Y
authors.lastname: Chen
mesh_terms: D000818:Animals; D002417:Cattle; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D003661:Decision Support Techniques; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D016678:Genome; D007774:Lactation / Q000235:genetics*; D008321:Mammary Glands, Animal / Q000378:metabolism*; D015398:Signal Transduction; D059467:Transcriptome / Q000235:genetics*
keywords: Bovine mammary; Coefficient of determination (CD); Decision coefficient (DC); Pathway analysis