Process / pipelineBioinformatics / omics
单细胞全基因组关联分析 (Single-cell GWAS) — 细胞类型特异性遗传关联分析
单细胞GWAS是一个整合的生物信息学流程，它将全基因组关联研究 (GWAS) 的信号映射到单细胞转录组图谱上，以识别哪些细胞类型和个体细胞承担了不成比例的疾病或性状遗传风险。通过利用单细胞RNA测序 (scRNA-seq) 图谱和GWAS汇总统计数据，它超越了组织层面的关联分析，揭示了疾病相关遗传变异发挥作用的精确细胞背景。
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来源
- Zhang, M. J., Hou, K., Dey, K. K., Sakaue, S., Jagadeesh, K. A., Weinand, K., ... & Price, A. L. (2022). Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data. Nature Genetics, 54(8), 1224-1234. link ↗
- Bryois, J., Calini, D., Macnair, W., Foo, L., Urich, E., Ortmann, W., ... & De Jager, P. L. (2022). Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nature Neuroscience, 25(8), 1104-1112. link ↗
如何引用本页
ScholarGate. (2026, June 3). Single-Cell Genome-Wide Association Study. ScholarGate. https://scholargate.app/zh/bioinformatics/single-cell-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.
- eQTL分析生物信息学↔ compare
- 全基因组关联研究 (GWAS)生物信息学↔ compare
- 通路富集分析生物信息学↔ compare
- RNA-seq差异表达生物信息学↔ compare
- 单细胞 eQTL 分析生物信息学↔ compare
- Single-cell RNA-seq analysis生物信息学↔ compare