Reconstructing physical cell interaction networks from single-cell data using Neighbor-seq

Bassel Ghaddar, Subhajyoti De

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Cell-cell interactions are the fundamental building blocks of tissue organization and multicellular life. We developed Neighbor-seq, a method to identify and annotate the architecture of direct cell-cell interactions and relevant ligand-receptor signaling from the undissociated cell fractions in massively parallel single cell sequencing data. Neighbor-seq accurately identifies microanatomical features of diverse tissue types such as the small intestinal epithelium, terminal respiratory tract, and splenic white pulp. It also captures the differing topologies of cancer-immune-stromal cell communications in pancreatic and skin tumors, which are consistent with the patterns observed in spatial transcriptomic data. Neighbor-seq is fast and scalable. It draws inferences from routine single-cell data and does not require prior knowledge about sample cell-Types or multiplets. Neighbor-seq provides a framework to study the organ-level cellular interactome in health and disease, bridging the gap between single-cell and spatial transcriptomics.

Original languageEnglish (US)
Article numberE82
JournalNucleic acids research
Issue number14
StatePublished - Aug 12 2022

All Science Journal Classification (ASJC) codes

  • Genetics


Dive into the research topics of 'Reconstructing physical cell interaction networks from single-cell data using Neighbor-seq'. Together they form a unique fingerprint.

Cite this