Public knowledge document

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

Motivation 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. Results 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. Availability and implementation NICHES

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

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

  • 引用:Raredon MSB, Yang J, Kothapalli N, Lewis W, Kaminski N, Niklason LE, Kluger Y. (2023). Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES. Bioinformatics (Oxford, England). PMID 36458905 · PMC9825783 · DOI 10.1093/bioinformatics/btac775
  • 证据类型:PRIMARY_RESEARCH
  • 主题:rna-seq、single-cell、spatial-omics
  • 被引次数(采集时):104
  • 原始记录:[Europe PMC](https://europepmc.org/article/MED/36458905)
  • 来源许可:[CC-BY](https://creativecommons.org/licenses/by/)
  • 作者摘要(按来源许可复用)

    Motivation 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. Results 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. Availability and implementation 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 information Supplementary data are available at Bioinformatics online.

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