Process / pipelineBioinformatics / omics
基于网络的全基因组关联研究 — Network-based GWAS
基于网络的GWAS将传统全基因组关联研究结果与生物网络数据（如蛋白质-蛋白质相互作用（PPI）网络或基因共表达图）相结合，以识别与疾病相关的基因模块或子网络。该方法不局限于报告单个最显著的SNP，而是通过分子相互作用网络传播关联信号，从而揭示那些即使单个变异未达到全基因组显著性水平，但其集体信号也与其复杂性状生物学相关的基因簇。
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来源
- Wang, Q., Yu, H., Zhao, Z., & Jia, P. (2015). EW_dmGWAS: edge-weighted dense module search for genome-wide association studies and gene expression profiles. Bioinformatics, 31(15), 2591–2594. link ↗
- Leiserson, M. D. M., Vandin, F., Wu, H.-T., Dobson, J. R., Eldridge, J. V., Thomas, J. L., Papoutsaki, A., Kim, Y., Niu, B., McLellan, M., Lawrence, M. S., Gonzalez-Perez, A., Tamborero, D., Cheng, Y., Ryslik, G. A., Lopez-Bigas, N., Getz, G., Ding, L., & Raphael, B. J. (2015). Pan-cancer network analysis identifies combinations of rare somatic mutations contributing to tumorigenesis. Nature Genetics, 47(2), 106–114. link ↗
如何引用本页
ScholarGate. (2026, June 3). Network-based Genome-Wide Association Study. ScholarGate. https://scholargate.app/zh/bioinformatics/network-based-gwas
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 拷贝数变异分析生物信息学↔ compare
- eQTL分析生物信息学↔ compare
- 基因集富集分析 (GSEA)生物信息学↔ compare
- 全基因组关联研究 (GWAS)生物信息学↔ compare
- 网络驱动的 eQTL 分析生物信息学↔ compare
- 通路富集分析生物信息学↔ compare