ABSTRACT

The recent development of a high throughput single-cell RNA sequence devises the opportunity to study entire transcriptomes in the smallest detail. It also leads to the characterization of molecules and subtypes of a cell. Cancer epigenetics induced not only from individual molecules but also from the dysfunction of the system and the coupling effect of genes. While rapid advances are being made in the development of tools for single-cell RNA-seq data analysis, few slants are noticed in the potential advantages of single-cell network construction.

Here, we used network perturbation theory with significant analysis to develop a cell-specific network that provides an insight into gene–gene association based on molecular expressions in a single-cell resolution. Besides, using this method, we can characterize each cell by inspecting how genes are connected and can identify the hub genes using network degree theory. Pathway & Gene enrichment analysis of the identified cell-specific high network degree genes supported the effectiveness of this method. This method could be beneficial for personalized drug design and even therapeutics.

摘要

最近开发的高通量单细胞 RNA 序列为以最小的细节研究整个转录组提供了机会。它还导致表征细胞的分子和亚型。癌症的表观遗传学不仅来自单个分子，还来自系统的功能障碍和基因的耦合效应。虽然单细胞 RNA-seq 数据分析工具的开发正在迅速取得进展，但在单细胞网络构建的潜在优势方面却很少有人注意到。

在这里，我们使用具有重要分析的网络扰动理论来开发细胞特异性网络，该网络基于单细胞分辨率中的分子表达提供对基因-基因关联的洞察。此外，使用这种方法，我们可以通过检查基因如何连接来表征每个细胞，并可以使用网络度理论识别中心基因。鉴定出的细胞特异性高网络度基因的通路和基因富集分析支持了该方法的有效性。这种方法可能有利于个性化药物设计甚至治疗。