Analysing the meta-interaction between pathways by gene set topological impact analysis

• Published in: BMC genomics Vol. 21; no. 1; pp. 748 - 12
• Main Authors: Yan, Shen, Chi, Xu, Chang, Xiao, Tian, Mengliang
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27.10.2020; BioMed Central; BMC
• Subjects: Algorithm development; Algorithms; Cellular signal transduction; Computational Biology; Crosstalk; Enrichment; Functional module; Gene expression; Gene Expression Profiling; Gene Regulatory Networks; Genetic aspects; Genetic research; Genomics; Genotypes; Health aspects; Impact analysis; Influence; Methodology; Modules; Signal Transduction; Topological pathway analysis; Topology; Transcriptome; China; Functional module; Algorithm development; Topological pathway analysis
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-020-07148-y

Pathway analysis is widely applied in transcriptome analysis. Given certain transcriptomic changes, current pathway analysis tools tend to search for the most impacted pathways, which provides insight into underlying biological mechanisms. Further refining of the enriched pathways and extracting functional modules by "crosstalk" analysis have been proposed. However, the upstream/downstream relationships between the modules, which may provide extra biological insights such as the coordination of different functional modules and the signal transduction flow have been ignored. To quantitatively analyse the upstream/downstream relationships between functional modules, we developed a novel GEne Set Topological Impact Analysis (GESTIA), which could be used to assemble the enriched pathways and functional modules into a super-module with a topological structure. We showed the advantages of this analysis in the exploration of extra biological insight in addition to the individual enriched pathways and functional modules. GESTIA can be applied to a broad range of pathway/module analysis result. We hope that GESTIA may help researchers to get one additional step closer to understanding the molecular mechanism from the pathway/module analysis results.