Unifying physical and molecular coordinate systems across modalities in spatial biology
- 1Fudan University
Abstract
Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.
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BibTeX
@misc{dai2026unifying,
title = {{Unifying physical and molecular coordinate systems across modalities in spatial biology}},
author = {B. Dai and Y. Yan and Z. Wang and Y. Liang and S. Li and P. Hu and X. Yang and C. Wang and L. Yi and C. Sun and J. Huang and X. Zhou and H. Chen and D. Zhang and Q. Zou and Y. Du and Z. Hu and Y. Xing and G. Cao and Z. Feng and J. Feng and S. Xu and W. Hu and Y. Zuo and B.-Z. Qian and Z. Yuan},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.01.748536},
url = {https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Unifying physical and molecular coordinate systems across modalities in spatial biology
AU - B. Dai
AU - Y. Yan
AU - Z. Wang
AU - Y. Liang
AU - S. Li
AU - P. Hu
AU - X. Yang
AU - C. Wang
AU - L. Yi
AU - C. Sun
AU - J. Huang
AU - X. Zhou
AU - H. Chen
AU - D. Zhang
AU - Q. Zou
AU - Y. Du
AU - Z. Hu
AU - Y. Xing
AU - G. Cao
AU - Z. Feng
AU - J. Feng
AU - S. Xu
AU - W. Hu
AU - Y. Zuo
AU - B.-Z. Qian
AU - Z. Yuan
PY - 2026
DA - 2026/09/01
PB - bioRxiv
DO - 10.64898/2026.09.01.748536
UR - https://www.biorxiv.org/content/10.64898/2026.09.01.748536v1
AB - Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.
ER -