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Updated: Sep 8, 2025

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波动结构预测全基因组扰动结果
Benjamin Kuznets-Speck1,2,3,4, Leon Schwartz1,2,3,4,5, Hanxiao Sun1,2,3,4
1Department of Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago IL, USA.
Research square
|August 20, 2025
概括
我们开发了CIPHER, 一种用于分析单细胞扰动屏幕中的基因表达数据的新框架. CIPHER使用基因协同波动来预测细胞如何应对干扰,从而提高生物洞察力.
科学领域:
- 功能性基因组学
- 系统生物学
- 统计物理
背景情况:
- 解释聚合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.
- 不被扰乱的细胞中的基因共波动可以为扰乱反应建模提供信息.
研究的目的:
- 介绍CIPHER (扰动和高维表达响应的共变推理),这是预测全转录组扰动结果的新框架.
- 利用线性响应理论和基因共波动来增强扰动屏幕的生物解释.
主要方法:
- 开发了CIPHER,一个使用线性响应理论和基因共波动的框架.
- 在合成网络和11个大规模单细胞扰动数据集 (4,234个扰动,>1.36M个细胞) 上验证.
- 使用贝叶斯推断来估计不确定性意识效应的大小.
主要成果:
- 通过利用基因共变性,CIPHER准确地对单个和双重扰动进行了全基因组应答.
- 消除基因对基因的共异性使模型的性能降低了11倍,突出显示了波动结构的重要性.
- 基因与基因的相关性可以在独立的研究中转移,这表明基因的波动模式得到保留.
- CIPHER在识别扰动方面表现优于差异表达量,并提供了不确定性意识的估计.
- 整个基因组的反应通过共变矩阵沿着~3个全球基因模块传播.
结论:
- 在理解复杂的生物反应方面, CIPHER 展示了理论模型的力量.
- 细胞波动模式为预测扰动结果提供了关键的基本设计原理.
- 利用基因协同波动为功能基因组学分析提供了更强大的方法.
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