INSISTC: Incorporating network structure information for single-cell type classification
INSISTC: Incorporating network structure information for single-cell type classification
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INSISTC：结合网络结构信息进行单细胞类型分类
DOI：
10.1016/j.ygeno.2022.110480
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发表时间：
2022
期刊：
影响因子：
4.4
通讯作者：
Hu, Haiyan
中科院分区：
文献类型：
--
作者：
Zheng, Hansi;Wang, Saidi;Li, Xiaoman;Hu, Haiyan
揭示单个细胞中的基因调控机制可以提供对细胞异质性和功能的洞察。最近积累的单细胞RNA-Seq数据使在单细胞分辨率下分析基因调控成为可能。了解特定细胞类型的基因调控有助于更准确地识别细胞类型和状态。利用这种关系的计算方法正在开发中。将基因调控机制发现与细胞类型分类相结合的方法在确定基因调控关系和整合基因调控网络结构等方面遇到了挑战。为了填补这一空白，我们开发了INSISTC，这是一种将基因调控网络结构信息纳入单细胞类型分类的计算方法。INSISTC能够在执行单细胞类型分类的同时识别特定细胞类型的基因调控机制。INSISTC证明了它在细胞类型分类中的准确性，以及它为深入了解个别细胞特有的分子机制提供的潜力。通过与其他方法的比较，证明了INSISTC在基因调控解释方面的互补性能。
Uncovering gene regulatory mechanisms in individual cells can provide insight into cell heterogeneity and function. Recent accumulated Single-Cell RNA-Seq data have made it possible to analyze gene regulation at single-cell resolution. Understanding cell-type-specific gene regulation can assist in more accurate cell type and state identification. Computational approaches utilizing such relationships are under development. Methods pioneering in integrating gene regulatory mechanism discovery with cell-type classification encounter challenges such as determine gene regulatory relationships and incorporate gene regulatory network structure. To fill this gap, we developed INSISTC, a computational method to incorporate gene regulatory network structure information for single-cell type classification. INSISTC is capable of identifying cell-type-specific gene regulatory mechanisms while performing single-cell type classification. INSISTC demonstrated its accuracy in cell type classification and its potential for providing insight into molecular mechanisms specific to individual cells. In comparison with the alternative methods, INSISTC demonstrated its complementary performance for gene regulation interpretation.