Evidence map›Paper›PMID 41867863›Full record

ArticlebioRxiv : the preprint server for biology2026

Toward Computationally Complete Spatial Omics.

Wei Li, Liran Mao, Yunhe Liu, Fuduan Peng, Nadja Sachs, Wenrui Wu, Stephanie Pei Tung Yiu, Hanying Yan, Amelia Schroeder, Xiaokang Yu and 24 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

34 authors.

Wei LiStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Liran MaoStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Yunhe LiuDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Fuduan PengDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Nadja SachsDepartment for Vascular and Endovascular Surgery, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Wenrui WuCenter for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Stephanie Pei Tung YiuCenter for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
Hanying YanStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Amelia SchroederStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Xiaokang YuStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Kaitian JinStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Shunzhou JiangStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Zihao ChenStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Melanie L LothStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Lorena GomezDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Idania LuboDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Niklas BlankArc Institute, Palo Alto, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA.
Laith Z SamarahDepartment of Chemistry, Princeton University, Princeton, NJ, USA.
Ankit BasakDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
Ye Won ChoDepartment of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA.
Chia-Yu ChenDepartment of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA.
David M KimDepartment of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA.
Alex K ShalekDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
Luisa Maren Solis SotoDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Joshua D RabinowitzDepartment of Chemistry, Princeton University, Princeton, NJ, USA.
Muredach P ReillyDivision of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Xuyu QianDepartment of Pediatrics, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Christoph A ThaissArc Institute, Palo Alto, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA.
Lars MaegdefesselDepartment for Vascular and Endovascular Surgery, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Linghua WangDepartment of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Humam KadaraDepartment of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Sizun JiangCenter for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-6149-3142
Yanxiang DengDepartment of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-9975-8086
Mingyao LiStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Cancer Immune Monitoring and Analysis CenterU24CA224331 · NCI · DANA-FARBER CANCER INST · PI FRANK S HODI, Catherine Ju-Ying Wu · 2017 to 2026
$18.4M
The Penn Human Precision Pain Center (HPPC): Discovery and Functional Evaluation of Human Primary Somatosensory Neuron Types at Normal and Chronic Pain ConditionsU19NS135528 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Mingyao Li, Wenqin Luo · 2023 to 2026
$11.2M
NHP CoreP01AI177687 · NIAID · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Boris Dominik Juelg · 2023 to 2026
$7.4M
Center for Gastric Pre-Cancer Atlas of Multidimensional Evolution in 3D (GAME3D)U01CA294518 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Paul F Mansfield, Linghua Wang · 2024 to 2026
$5.4M
Defining Mechanisms of Viral Persistence in Situ at the Single-Cell LevelR01AI149672 · NIAID · OREGON HEALTH & SCIENCE UNIVERSITY · PI ESTES, JACOB D · 2020 to 2024
$4.0M
Spatial-Temporal Dissection of Stratified Host Tissue Responses to Severe acute respiratory syndrome-related coronaviruses in situ to Understand Intra-host PathogenesisDP2AI171139 · NIAID · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Sizun Jiang · 2022 to 2026
$2.3M
Integrative analysis of spatial transcriptomics with histology images and single cellsR01HG013185 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI Mingyao Li · 2023 to 2026
$2.2M
Integration of spatial transcriptomics, genetics, and histomorphology for causal inference in atherosclerotic cardiovascular diseaseR01HL171595 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Muredach P Reilly · 2024 to 2026
$2.0M
High-spatial-resolution multi-omics sequencing of brain lesions in multiple sclerosisDP2AI177913 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI Yanxiang Deng · 2023 to 2026
$1.8M
Dissecting Orchestrated Immune Responses to Glioblastoma within the Native Tissue Microenvironment to Improve Treatment OutcomesR01NS139479 · NINDS · BETH ISRAEL DEACONESS MEDICAL CENTER · PI VASSILIKI A BOUSSIOTIS, Alain Charest · 2025 to 2026
$1.4M
Statistical Power Analysis Framework for Multi-Sample and Cross-Platform Spatial Omics ExperimentsR01GM152585 · NIGMS · OHIO STATE UNIVERSITY · PI Dongjun Chung, Qin Ma · 2024 to 2026
$1.2M
Developing informatics tools to predict virtual spatial transcriptomics data with single-cell resolution in large-scale studiesR01LM014592 · NLM · UNIVERSITY OF PENNSYLVANIA · PI Mingyao Li · 2024 to 2026
$1.1M
NCI NIH HHS U01 CA294518NCI NIH HHS U24 CA224331NHGRI NIH HHS R01 HG013185NHLBI NIH HHS R01 HL171595NIAID NIH HHS DP2 AI171139NIAID NIH HHS DP2 AI177913NIAID NIH HHS P01 AI177687NIAID NIH HHS R01 AI149672NIGMS NIH HHS R01 GM152585NINDS NIH HHS R01 NS139479NINDS NIH HHS U19 NS135528NLM NIH HHS R01 LM014592
6 · The paper itself

Abstract

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

Indexed as

Deep learningIntegrationMultimodal spatial omicsPredictionVirtual tissue model

Identifiers

PMID41867863
PMCPMC13001418

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.