在单细胞多模式测序和多omics数据集成方面的进展
Xuefei Wang1, Xinchao Wu1, Ni Hong1
1Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
Biophysical reviews
|March 18, 2024
概括
单细胞多式欧米克技术从一个细胞中对多个分子层进行分析,克服信息碎片化. 整合这些数据将建立一个全面的细胞地图,以了解基因调节和疾病.
科学领域:
- 单细胞生物学 单细胞生物学
- 多omics数据集成多omics数据集成
- 基因组学和表观基因组学
背景情况:
- 单细胞测序的进步使细胞异质性的剖析成为可能.
- 单组学方法提供了碎片化的信息,限制了全面的细胞状态分析.
- 需要采用综合方法来捕获完整的细胞信息.
研究的目的:
- 审查单细胞多式联络的实验方法.
- 总结用于多omics数据集成的计算方法.
- 讨论单细胞多组学领域的未来方向.
主要方法:
- 来自单细胞的基因组,转录组,表观基因组和蛋白质组的联合分析实验技术的概述.
- 用于整合多种单细胞欧米克数据集的计算策略的摘要.
- 讨论数据整合的挑战和机遇.
主要成果:
- 单细胞多式联络使得分子层的同时研究成为可能.
- 多omics数据的整合揭示了基因组/表观遗传变化和基因表达/翻译之间的联系.
- 在单细胞分辨率下发现疾病致病机制的潜力.
结论:
- 单细胞多式欧米克技术提供了对细胞状态的整体视图.
- 数据整合对于充分利用多领域数据的全部潜力至关重要.
- 未来,公共多主题数据的整合将使一个全面的细胞地图成为可能.
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