Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06511, USA.
Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA.
Bioinformatics. 2023 Jan 1;39(1). doi: 10.1093/bioinformatics/btac775.
Recent years have seen the release of several toolsets that reveal cell-cell interactions from single-cell data. However, all existing approaches leverage mean celltype gene expression values, and do not preserve the single-cell fidelity of the original data. Here, we present NICHES (Niche Interactions and Communication Heterogeneity in Extracellular Signaling), a tool to explore extracellular signaling at the truly single-cell level.
NICHES allows embedding of ligand-receptor signal proxies to visualize heterogeneous signaling archetypes within cell clusters, between cell clusters and across experimental conditions. When applied to spatial transcriptomic data, NICHES can be used to reflect local cellular microenvironment. NICHES can operate with any list of ligand-receptor signaling mechanisms, is compatible with existing single-cell packages, and allows rapid, flexible analysis of cell-cell signaling at single-cell resolution.
NICHES is an open-source software implemented in R under academic free license v3.0 and it is available at http://github.com/msraredon/NICHES. Use-case vignettes are available at https://msraredon.github.io/NICHES/.
Supplementary data are available at Bioinformatics online.
近年来，已经有几个工具集可以从单细胞数据中揭示细胞间相互作用。然而，所有现有的方法都利用了平均细胞类型基因表达值，并没有保留原始数据的单细胞保真度。在这里，我们提出了 NICHES（细胞外信号的生态位相互作用和通信异质性），这是一种在真正的单细胞水平上探索细胞外信号的工具。
NICHES 允许嵌入配体-受体信号代理，以可视化细胞群内、细胞群之间和实验条件之间的异质信号原型。当应用于空间转录组学数据时，NICHES 可以用来反映局部细胞微环境。NICHES 可以与任何配体-受体信号机制列表一起使用，与现有的单细胞包兼容，并允许以单细胞分辨率快速、灵活地分析细胞间信号。
NICHES 是一个用 R 编写的开源软件，根据学术免费许可证 v3.0 发布，可在 http://github.com/msraredon/NICHES 上获得。用例简介可在 https://msraredon.github.io/NICHES/ 上获得。
补充数据可在生物信息学在线获得。
