Characterization of spatial homogeneous regions in tissues with concordex

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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Publication Details

Journal
BMC Methods
Published
2026-06-30
DOI
https://doi.org/10.1186/s44330-026-00086-3
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Characterization of spatial homogeneous regions in tissues with concordex

Tara Chari, Lior Pachter, Kayla Jackson, Ángel Gálvez-Merchán et al.
BMC Methods
Single-cell and spatial transcriptomics
article

Characterization of spatial homogeneous regions in tissues with concordex

Tara Chari, Lior Pachter, Kayla Jackson, Ángel Gálvez-Merchán, Lambda Moses, A. Sina Booeshaghi, Alexandra Kim, Orhan Hosten-Mittermaier
article en

Abstract

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 .

BMC MethodsVol. 3(1)
Broad Institute (US), University of Southern California (US), California Institute of Technology (US), Genesis Foundation (US), Columbia University (US), University of California, Berkeley (US), Stanford University (US)
California Institute of Technology, National Institutes of Health
Openalex Percentile: Top 11%
Single-cell and spatial transcriptomics
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