Evidence map›Paper›PMID 42370255›Full record

ArticleResearch square2026

Cross-Modality Alignment of Spatial Transcriptomics, Multiplexed Imaging, and Histology with PHARAOH.

Sicong Yao, Zehua Jing, Shunzhou Jiang, Wei Li, Yoshiaki Yamamoto, Bernhard Dumoulin, Nadja Sachs, Lars Maegdefessal, Katalin Susztak, Linghua Wang and 2 more

Abstract readPreprint
In one paragraph

Article in Research square, 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

12 authors.

Sicong YaoStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Zehua JingStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-7275-0869
Shunzhou JiangStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0009-0000-7309-2389
Wei LiStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-9186-1142
Yoshiaki YamamotoStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Bernhard DumoulinRenal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
Nadja SachsDepartment for Vascular and Endovascular Surgery, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.ORCID 0000-0001-8031-017X
Lars MaegdefessalGerman Center for Cardiovascular Research (DZHK), Berlin, Germany; partner site Munich Heart Alliance, Germany.ORCID 0000-0001-5228-2634
Katalin SusztakRenal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-1005-3726
Linghua WangDepartment of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0001-9380-0266
Humam KadaraThe University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, TX, USA.ORCID 0000-0003-2976-9115
Mingyao LiStatistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0001-8180-0621

Funding

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
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
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 CA294518NHGRI NIH HHS R01 HG013185NHLBI NIH HHS R01 HL171595NLM NIH HHS R01 LM014592
6 · The paper itself

Abstract

Accurate cross-modality alignment between spatial transcriptomics (ST), multiplexed imaging, and histology is essential for spatially contextualized molecular analysis. In imaging-based ST platforms, molecular measurements are defined in the coordinate system of nuclear-stained images rather than in histological space, requiring precise registration for accurate integration with tissue morphology. Existing approaches either rely on labor-intensive manual landmark placement or lack the precision required for cellular-resolution alignment. Here we present PHARAOH, a hierarchical framework for cross-modality alignment of ST, multiplexed imaging, and histology. By combining global structural alignment with automated nuclear landmark anchoring, PHARAOH enables accurate coordinate transfer between molecular imaging and histological space with minimal user input. Across diverse tissue types, imaging platforms, and staining conditions, PHARAOH consistently achieved fast, robust, and spatially precise alignment, including across adjacent tissue sections. The framework further generalizes to multiplexed immunofluorescence imaging, providing a unified and scalable strategy for integrating spatial molecular measurements with histological architecture.

Identifiers

PMID42370255
PMCPMC13308372

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.