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Peer-reviewedCC BYBMC Methods

Characterization of spatial homogeneous regions in tissues with concordex

  • Kayla C. Jackson1,2
  • A. Sina Booeshaghi3
  • Ángel Gálvez-Merchán4
  • Lambda Moses5
  • Tara Chari6
  • Alexandra Kim7
  • Orhan Hosten-Mittermaier8
  • Lior S. Pachter9,1
9 affiliations
  1. 1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
  2. 2Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
  3. 3Department of Bioengineering, University of California, Berkeley, CA, USA
  4. 4Cellarity, Boston, MA, USA
  5. 5Department of Statistics, Columbia University, New York, NY, USA
  6. 6Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
  7. 7Polytechnic High School, Pasadena, CA, USA
  8. 8The College Preparatory School, Oakland, CA, USA
  9. 9Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
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Abstract

The rapid advancement of spatially resolved transcriptomics (SRT) technologies has facilitated exploration of how gene expression varies across tissues. However, identifying spatially variable genes remains challenging due to confounding variation introduced by the spatial distribution of cell types. We introduce a new approach to identifying spatial domains that are homogeneous with respect to cell-type composition that facilitates the decomposition of gene expression patterns by cell-type and spatial variation. Our method, called concordex, is efficient and effective across technological platforms and tissue types, and using several biological datasets we show that it can be used to identify genes with subtle variation patterns that are missed when considering only cell-type variation, or spatial variation, alone. The concordex tool is freely available at https://github.com/pachterlab/concordexR.

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Cite

BibTeXRIS
BibTeX
@article{jackson2026characterization,
  title = {{Characterization of spatial homogeneous regions in tissues with concordex}},
  author = {Kayla C. Jackson and A. Sina Booeshaghi and Ángel Gálvez-Merchán and Lambda Moses and Tara Chari and Alexandra Kim and Orhan Hosten-Mittermaier and Lior S. Pachter},
  journal = {BMC Methods},
  year = {2026},
  month = jun,
  doi = {10.1186/s44330-026-00086-3},
  url = {https://doi.org/10.1186/s44330-026-00086-3},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Characterization of spatial homogeneous regions in tissues with concordex
AU  - Kayla C. Jackson
AU  - A. Sina Booeshaghi
AU  - Ángel Gálvez-Merchán
AU  - Lambda Moses
AU  - Tara Chari
AU  - Alexandra Kim
AU  - Orhan Hosten-Mittermaier
AU  - Lior S. Pachter
PY  - 2026
DA  - 2026/06/30
JO  - BMC Methods
DO  - 10.1186/s44330-026-00086-3
UR  - https://doi.org/10.1186/s44330-026-00086-3
AB  - The rapid advancement of spatially resolved transcriptomics (SRT) technologies has facilitated exploration of how gene expression varies across tissues. However, identifying spatially variable genes remains challenging due to confounding variation introduced by the spatial distribution of cell types. We introduce a new approach to identifying spatial domains that are homogeneous with respect to cell-type composition that facilitates the decomposition of gene expression patterns by cell-type and spatial variation. Our method, called concordex, is efficient and effective across technological platforms and tissue types, and using several biological datasets we show that it can be used to identify genes with subtle variation patterns that are missed when considering only cell-type variation, or spatial variation, alone. The concordex tool is freely available at https://github.com/pachterlab/concordexR.
SN  - 3004-8729
ER  -