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Updated: Sep 16, 2025

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波动结构预测了全基因组扰动结果
bioRxiv : the preprint server for biology
|July 9, 2025
概括
我们开发了CIPHER,一种使用基因共同波动来预测细胞对遗传干扰反应的新方法. 这种方法利用基线基因共变性来获得强大的功能基因组学见解.
科学领域:
- 功能性基因组学 功能性基因组学
- 系统生物学 系统生物学
- 统计物理 统计物理
背景情况:
- 解释聚合的单细胞扰动屏幕是一个挑战.
- 目前的方法要么是不透明的深度学习模型,要么是过于简单的框架.
- 在未受到干扰的细胞中,基因共同波动为建模干扰反应提供了一个有希望的途径.
研究的目的:
- 介绍CIPHER (扰动和高维表达响应的共变推理),用于预测全转录组扰动结果的框架.
- 为了利用线性反应理论和基因共同波动来得出强有力的生物学结论.
主要方法:
- 开发了CIPHER,一个使用线性响应理论的概念框架.
- 将CIPHER应用于合成网络和11个大规模单细胞扰动数据集 (4,234个扰动,>1.36M个细胞).
- 通过比较基因共变性基于基因共变性和没有基线基因共变性的预测来验证模型性能.
主要成果:
- 通过利用基线基因协同变异,CIPHER准确地回顾了整个基因组对单一和双重扰动的反应.
- 删除基因-基因共变性使模型性能降低了11倍,突出显示了波动结构的重要性.
- 基因-基因相关性被证明可以在同一个细胞类型的独立实验中转移.
- 通过贝叶斯推理,CIPHER的表现优于差异表达度量,并通过贝叶斯推理提供了不确定性意识效应大小估计.
- 全基因组的反应通过共变矩阵沿着大约三个独立的基因模块传播.
结论:
- CIPHER展示了理论基础模型在捕捉复杂的生物反应中的力量.
- 基线基因波动模式编码了对于理解细胞反应至关重要的基本设计原则.
- 利用基因协同波动为功能基因组学提供了强大的和可解释的方法.
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