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Updated: May 20, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Knowledge enrichment analysis for human tissue-specific genes uncover new biological insights
Xiu-Jun Gong1, Hua Yu, Chun-Bai Yang
1School of Computer Science and Technology, Tianjin University, Weijin Rd No. 92, Nankan, Tianjin, 300072, China. gongxj@tju.edu.cn
Abstract:
The expression and regulation of genes in different tissues are fundamental questions to be answered in biology. Knowledge enrichment analysis for tissue specific (TS) and housekeeping (HK) genes may help identify their roles in biological process or diseases and gain new biological insights. In this paper, we performed the knowledge enrichment analysis for 17,343 genes in 84 human tissues using Gene Set Enrichment Analysis (GSEA) and Hypergeometric Analysis (HA) against three biological ontologies: Gene Ontology (GO), KEGG pathways and Disease Ontology (DO) respectively. The analyses results demonstrated that the functions of most gene groups are consistent with their tissue origins. Meanwhile three interesting new associations for HK genes and the skeletal muscle tissue genes are found. Firstly, Hypergeometric analysis against KEGG database for HK genes disclosed that three disease terms (Parkinson's disease, Huntington's disease, Alzheimer's disease) are intensively enriched. Secondly, Hypergeometric analysis against the KEGG database for Skeletal Muscle tissue genes shows that two cardiac diseases of "Hypertrophic cardiomyopathy (HCM)" and "Arrhythmogenic right ventricular cardiomyopathy (ARVC)" are heavily enriched, which are also considered as no relationship with skeletal functions. Thirdly, "Prostate cancer" is intensively enriched in Hypergeometric analysis against the disease ontology (DO) for the Skeletal Muscle tissue genes, which is a much unexpected phenomenon.

