摘要
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.
基金
This work was supported by the Rutgers School of Public Health Pilot Grant,USA,the Rutgers Busch Biomedical Grant,USA,and the New Jersey Alliance for Clinical and Translational Science Mini-methods Grant(a component of the US National Institutes of Health under Grant No.UL1TR0030117),USA,to WVL
Computational resources were provided by the Office of Advanced Research Computing at Rutgers,The State University of New Jersey,USA,under the National Institutes of Health Grant No.S10OD012346.
