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Comprehensive visualization of cell-cell interactions in single-cell and spatial transcriptomics with NICHES.
Raredon, Micha Sam Brickman; Yang, Junchen; Kothapalli, Neeharika; Lewis, Wesley; Kaminski, Naftali; Niklason, Laura E; Kluger, Yuval.
Afiliação
  • Raredon MSB; Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06511, USA.
  • Yang J; Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA.
  • Kothapalli N; Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, CT 06511, USA.
  • Lewis W; Department of Immunobiology, Yale University, New Haven, CT 06511, USA.
  • Kaminski N; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
  • Niklason LE; Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, CT 06511, USA.
  • Kluger Y; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA.
Bioinformatics ; 39(1)2023 01 01.
Article em En | MEDLINE | ID: mdl-36458905
ABSTRACT
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Transcriptoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article