Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.


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 Use-case vignettes are available at Supplementary data are available at Bioinformatics online.


Spatial Transcriptomics

MeSH terms

Gene Expression Profiling
Cell Communication


Raredon, Micha Sam Brickman
Yang, Junchen
Kothapalli, Neeharika
Lewis, Wesley
Kaminski, Naftali
Niklason, Laura E
Kluger, Yuval