CEMIG:使用ATAC-seqq的德布莱恩图表预测cis调节动机
Yizhong Wang1, Yang Li2, Cankun Wang2
1School of Mathematics, Shandong University, Jinan, 250100, China.
Briefings in bioinformatics
|January 8, 2024
概括
CEMIG是一种新的算法,它使用ATAC-seq数据改进了对转录因子 (TF) 结合动机的发现. 它准确地识别了细胞类型特定和常见的动机,推进了基因组研究.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 识别转录因子 (TF) 结合动机对于理解基因调节至关重要.
- 虽然ATAC-seq被广泛用于染色质可访问性,但计算模式发现方法需要改进.
- 现有的算法往往侧重于TF结合足迹,而不是全面的动机发现.
研究的目的:
- 通过使用de Bruijn图 (CEMIG) 引入Cis rRegulatory Motif Influence,这是一个用于TF结合动机发现和映射的新算法.
- 通过使用ATAC-seq数据集,对CEMIG的表现进行评估,并与已建立的方法进行比较.
- 为了证明CEMIG在识别细胞类型特异性和进化保存的基因方面的能力.
主要方法:
- 开发了CEMIG,一种利用de Bruijn和Hamming距离图范式的算法.
- 应用CEMIG到来自Cistrome数据浏览器的129个ATAC-seq数据集进行性能评估.
- 通过转录和功能基因组研究验证已识别的基因.
主要成果:
- 在四个评估指标中,CEMIG显著超过了三种既定方法.
- 该算法在GM12878和K562细胞系中准确地识别了细胞类型特定的和常见的TF动机.
- 功能性基因组研究证实了CEMIG识别的动机的生物学相关性.
结论:
- CEMIG提供了一种优越的方法,用于从ATAC-seq数据中发现和映射图案.
- 该算法增强了功能相关的TF绑定站点的识别.
- CEMIG提供了一个强大的,跨平台兼容的基因组序列分析工具.
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