PuSH - Publikationsserver des Helmholtz Zentrums München

Birk, S. ; Bonafonte Pardás, I. ; Feriz, A.M.* ; Boxall, A.* ; Agirre, E.* ; Memi, F.* ; Maguza, A.* ; Yadav, A.* ; Armingol, E.* ; Fan, R.* ; Castelo-Branco, G.* ; Theis, F.J. ; Bayraktar, O.A.* ; Talavera-López, C.* ; Lotfollahi, M.

Quantitative characterization of cell niches in spatially resolved omics data.

Nat. Genet. (2025)
DOI PMC
Spatial omics enable the characterization of colocalized cell communities that coordinate specific functions within tissues. These communities, or niches, are shaped by interactions between neighboring cells, yet existing computational methods rarely leverage such interactions for their identification and characterization. To address this gap, here we introduce NicheCompass, a graph deep-learning method that models cellular communication to learn interpretable cell embeddings that encode signaling events, enabling the identification of niches and their underlying processes. Unlike existing methods, NicheCompass quantitatively characterizes niches based on communication pathways and consistently outperforms alternatives. We show its versatility by mapping tissue architecture during mouse embryonic development and delineating tumor niches in human cancers, including a spatial reference mapping application. Finally, we extend its capabilities to spatial multi-omics, demonstrate cross-technology integration with datasets from different sequencing platforms and construct a whole mouse brain spatial atlas comprising 8.4 million cells, highlighting NicheCompass' scalability. Overall, NicheCompass provides a scalable framework for identifying and analyzing niches through signaling events.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Common Coordinate Framework; Expression; Morphogenesis
ISSN (print) / ISBN 1061-4036
e-ISSN 1546-1718
Zeitschrift Nature Genetics
Verlag Nature Publishing Group
Verlagsort New York, NY
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of AI for Health (AIH)
Förderungen Joint Federal and State Support Program for Young Academics (WISNA)
Faculty of Medicine of the Julius-Maximilian-Universitat Wuerzburg
Swedish Brain Foundation
Swedish Cancer Society (Cancerfonden)
Knut and Alice Wallenberg Foundation
Joachim Herz Stiftung
Helmholtz Association
Wellcome Trust