MINGLE:基于相互信息的可解释框架,用于在单细胞染色体可访问性数据中自动注释细胞类型
Siyu Li1, Yifan Huang1, Shengquan Chen2
1School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, China.
Genome biology
|June 11, 2025
概括
MINGLE通过使用细胞相似性和拓学准确注释细胞类型来增强单细胞染色体可访问性测序 (scCAS) 分析. 这种可解释的框架还可以识别新型细胞类型,提供有价值的生物学见解.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 表观遗传学 在表观遗传学中,表观遗传学是指表观遗传学.
背景情况:
- 单细胞染色体可访问性测序 (scCAS) 对于理解表观基因异质性至关重要.
- 现有的方法在准确注释各种细胞类型,特别是罕见或新型细胞方面面临挑战.
研究的目的:
- 引入MINGLE,这是一个可解释的框架,用于对scCAS数据进行准确的细胞类型注释.
- 开发一种新的策略,在scCAS数据集中识别以前未被发现的细胞类型.
- 为了增强从scCAS数据分析中获得的生物见解.
主要方法:
- 开发了MINGLE,这是一个基于相互信息的框架,利用细胞相似性和拓结构.
- 实施基于凸体外的战略,用于新型细胞类型识别.
- 进行了广泛的实验,以评估MINGLE的性能与现有方法相比.
主要成果:
- MINGLE表现出卓越的细胞类型注释准确性,特别是在罕见和新型细胞类型.
- 该框架提供了有价值的生物见解,性能优于当前的注释工具.
- 在跨批,跨组织和跨物种数据集中,MINGLE表现出强度和多功能性,有效地处理数据不平衡和大小变化.
结论:
- 在scCAS数据中,MINGLE为复杂的细胞类型注释任务提供了通用和准确的解决方案.
- 该框架识别新型细胞类型的能力为生物发现开辟了新的途径.
- 在各种数据场景中MINGLE的表现强调了其在表观基因组研究中的广泛适用性.
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