Neighborhood nonnegative matrix factorization identifies patterns and spatially-variable genes in large-scale spatial transcriptomics data

Abstract excerpt

Tissues consist of multi-cellular neighborhoods in which different cell types express correlated gene programs due to shared signaling environments. Methods for identifying these spatial neighborhoods may be powerful, but currently do not scale to existing data sets of millions of cells and often artificially divide tissues into distinct neighborhoods with hard borders. To better identify multi-cellular microenvir...

Topics

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• Algorithms
• Cluster Analysis
• Neural Networks, Computer
• Phenotype

Identifiers and source

Literature Corpus work

0c6df514-8b75-5398-9108-bd7642f88c2c

DOI

10.1101/2025.04.26.650724