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bioRxiv · 10.1101/2020.09.19.304956

scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data

Li, W. V.·Li, Y.
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Abstract

A system-level understanding of the regulation and coordination mechanisms of gene expression is essential to understanding 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 to 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 source code used in this article is available at https://github.com/Vivianstats/scLink.

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Li, W. V., Li, Y.. 2020-09-20. scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data. https://doi.org/10.1101/2020.09.19.304956

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