A system-level understanding of the regulation and coordination mechanisms of gene expression is essential for studying the complexity of biological processes in health and disease. With the rapid development of single-cell RNA sequencing technologies, it is now possible to investigate gene interactions in a cell type-specific manner. Here we propose the scLink method, which uses statistical network modeling to understand the co-expression relationships among genes and construct sparse gene co-expression networks from single-cell gene expression data. We use both simulation and real data studies to demonstrate the advantages of scLink and its ability to improve single-cell gene network analysis. The scLink R package is available at https://github.com/Vivianstats/scLink.

对基因表达的调控和协调机制的系统级理解对于研究健康和疾病中生物过程的复杂性至关重要。随着单细胞 RNA 测序技术的快速发展，现在可以以特定细胞类型的方式研究基因相互作用。在这里，我们提出了 scLink 方法，该方法使用统计网络建模来了解基因之间的共表达关系，并从单细胞基因表达数据中构建稀疏的基因共表达网络。我们使用模拟和真实数据研究来证明 scLink 的优势及其改进单细胞基因网络分析的能力。scLink R 包可在 https://github.com/Vivianstats/scLink 获得。