Evidence map›Paper›PMID 41505103›Full record

ArticleNucleic acids research2026

CellMap: precision mapping of cellular landscape in spatial transcriptomics.

Hongjia Liu, Huamei Li, Amit Sharma, Guoyan Tang, Zongyu Xie, Yunyao Shen, Qiong Li, Chen Gong, Xiao Sun, Kun Luo and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Hongjia LiuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Huamei LiDepartment of General Surgery, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, PR China.
Amit SharmaDepartment of Integrated Oncology, Center for Integrated Oncology, University Hospital of Bonn, Bonn 53127, Germany.ORCID 0000-0002-2216-5389
Guoyan TangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Zongyu XieState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Yunyao ShenState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Qiong LiState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.
Chen GongState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.ORCID 0009-0004-1367-6349
Xiao SunState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.ORCID 0000-0003-1048-7775
Kun LuoDepartment of Neurosurgery, the First affiliated hospital of Xinjiang Medical University, Urumqi 830054, PR China.
Hongde LiuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, PR China.ORCID 0000-0001-8768-764X

Funding

Leading Technology Program of Jiangsu Province BK20222008National Natural Science Foundation of China 62401272Xinjiang Uygur Autonomous Region 2023TSYCLJ0030Xinjiang Uygur Autonomous Region 2025B03015Xinjiang Uygur Autonomous Region Tianshan Talent
6 · The paper itself

Abstract

Integrating single-cell RNA sequencing and spatial transcriptomics is the current imperative to manually explore the landscape of cellular mixtures. Herein, we developed CellMap (https://github.com/liuhong-jia/CellMap), a computational tool that allows spatial transcriptomic spots to be resolved at single-cell resolution. CellMap combines strategies that incorporate the co-linearity of seed genes, the random forest model, and the linear assignment algorithm to achieve optimal assignment of single cells to spatial spots. Using comprehensive benchmarking across various platforms and tissue types, we demonstrated that CellMap outperforms existing methods.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisSoftwareTranscriptomeAlgorithmsAnimalsHumansRandom ForestSequence Analysis, RNASingle-Cell Gene Expression AnalysisSpatial Transcriptomics

Identifiers

PMID41505103
PMCPMC12781899

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.