关于从ATAC-seq数据中识别差异活性转录因子的识别
Felix Ezequiel Gerbaldo1, Emanuel Sonder1,2,3,4, Vincent Fischer5
1Computational Neurogenomics, D-HEST Institute for Neurosciences, Zürich, Switzerland.
bioRxiv : the preprint server for biology
|March 18, 2024
概括
本研究对使用ATAC-seq数据识别活跃转录因子 (TF) 的方法进行了基准测试. 确定了分析TF活动及其对DNA可访问性的影响的三个有前途的方法.
科学领域:
- 表观基因组学是指表观基因组学.
- 计算生物学 计算生物学
- 分子生物学分子生物学
背景情况:
- 使用测序 (ATAC-seq) 检测转化酶可访问染色质是一种关键的表观基因组分析技术.
- 识别活跃的转录因子 (TF) 对于理解生物现象至关重要.
- 从ATAC-seq数据推断TF活动的最佳方法仍未得到充分探索.
研究的目的:
- 从ATAC-seq数据中比较和比较各种计算方法来识别差异活跃的TF.
- 确定TF活动推断和DNA可访问性分析的最有效方法.
- 评估TF枯竭对DNA可访问性的影响,使用一种新的实验系统.
主要方法:
- 使用精心策划的ATAC-seq数据集和半模拟,对多种TF识别方法进行比较.
- 包括专门的和重新设计的计算工具用于TF活动分析.
- 研究方法变化,无核素体片段的使用,以及技术变化的影响.
主要成果:
- 确定了三个非常有前途的方法:修改的chromVAR-limma工作流程,monaLisa和GC校正的多变量建模方法.
- 证明这些方法在分析TF扰动及其对DNA可访问性的影响方面的实用性.
- 描述TRAnscription Factor TTargeting Chimeras (TRAFTAC) 对NFkBDNA结合可访问性的影响.
结论:
- 该研究提供了对从ATAC-seq数据中推断TF活动方法的强有力的评估.
- 推的工作流提供了提高TF分析的准确性和可靠性.
- 这些发现有助于更深入地了解TF介导的基因调节和染色质可访问性动态.
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