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克罗姆-Sig:通过信号处理方法消除噪音的一维基因组资料
Nandita J Gupta1,2, Zachary Apell3,2, Minji Kim2,1
1Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA.
bioRxiv : the preprint server for biology
|August 20, 2025
概括
Chrom-Sig是一个新的Python包,可以有效地消除基因组测序数据 (如ChIP-seq和ATAC-seq) 中的技术噪音,而不需要对照样本. 这个工具可以帮助研究人员准确地识别数据中的真实生物信号.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 像ChIP-seq,CUT&Tag,CUT&RUN和ATAC-seq这样的下一代测序 (NGS) 技术对于现代基因组研究至关重要.
- 这些实验产生覆盖范围数据,用于分析转录因子结合和染色质可访问性.
- 实验协议中固有的技术噪声使生物信号的准确提取变得复杂.
研究的目的:
- 开发一个统计严格和计算高效的方法来消除1D基因组覆盖轨道的噪音.
- 提供一种不需要先前假设或实验控制 (例如输入或尖端控制) 的工具.
主要方法:
- 开发Chrom-Sig,这是一个用于消除基因组覆盖数据噪音的Python包.
- 使用实证零分布的计算来区分信号与噪声.
- 在各种数据集上进行测试,包括ChIP-seq,CUT&RUN,ATAC-seq和snATAC-seq.
主要成果:
- Chrom-Sig有效地将基因组数据分解为信号和噪声组件.
- 该包可以有效地执行消除噪音和峰值调用,通常在1-2小时内使用~20GB的内存.
- 来自CTCF CUT&RUN,ATAC-seq和RNA聚合酶II实验的无噪声数据显示了与已知的调节元素和动机具有生物学意义的相关性.
结论:
- Chrom-Sig为各种NGS技术产生的基因组覆盖轨道消除噪音提供了一种多功能和通用解决方案.
- 该工具提高了基因组数据中信号检测的准确性,促进了下游生物解释.
- Chrom-Sig 是公开的,促进其在研究界的采用.
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