A decision analysis model for KEGG pathway analysis

Abstract

BackgroundThe 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.ResultsA 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.ConclusionsA 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1285-1) contains supplementary material, which is available to authorized users.

Identification of the Spinal Expression Profile of Non-coding RNAs Involved in Neuropathic Pain Following Spared Nerve Injury by Sequence Analysis

“…The Gene Ontology (GO) is a major bioinformatics tool that unifies the representation of genes and gene product attributes across all species (Altshuler et al, 2008). GO terms and GO annotations have proven to be good predictors of gene function and trend (Li et al, 2009; Du et al, 2016). KEGG pathway databases store the higher order functional information for systematic analysis of gene functions and are more widely used in current enrichment analysis platforms (Camon et al, 2004).…”

Detecting Sustainability of Desertification Reversion: Vegetation Trend Analysis in Part of the Agro-Pastoral Transitional Zone in Inner Mongolia, China

“…It is widely used to describe direct and indirect factors to dependent variable. More detailed explanation can be found in the investigation [49]. The coefficient of …”

Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

“…Since in this study, we focused on the biological features underlying the candidate genes, only the GO category of biological process was analyzed. For pathway analysis, the Kyoto Gene and Genome Encyclopedia (Du et al, 2016;KEGG) F I G U R E 1 PRISMA flow diagram illustrating search strategy and studies included in the analysis. Both GO and pathway enrichment analysis were finished by the ToppFun module of ToppGene (http://toppg ene.cchmc.org; Chen, Bardes, Bardes, Aronow, & Jegga, 2009).…”

“…Then, the enriched items were subjected to REVIGO (Supek, Bosnjak, Bosnjak, Škunca, & Šmuc, 2011;http://revigo.irb.hr/) to remove the redundant GO terms and obtained a list of nonredundant GO biological process terms enriched in the candidate genes. For pathway analysis, the Kyoto Gene and Genome Encyclopedia (Du et al, 2016;KEGG) F I G U R E 1 PRISMA flow diagram illustrating search strategy and studies included in the analysis. PRISMA is Preferred Reporting Items for Systematic Reviews and Meta-Analyses (http://www.prisma-state ment.org/) PATHWAY was adopted as the pathway database, and a FDR threshold of 0.05 was used to define a significant pathway.…”