Evidence map›Paper›PMID 41193576›Full record

ArticleCommunications biology2025

CellSP enables module discovery and visualization for subcellular spatial transcriptomics data.

Bhavay Aggarwal, Saurabh Sinha

Abstract read
In one paragraph

Article in Communications biology, 2025. 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. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Bhavay AggarwalThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.ORCID http://orcid.org/0009-0005-4399-3158
Saurabh SinhaThe Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA. saurabh.sinha@bme.gatech.edu.ORCID http://orcid.org/0000-0001-6033-7746

Funding

Quantitative Regulatory Genomics: Networks, CIS-Regulatorycodes, and Phenotypic VariationR35GM131819 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SINHA, SAURABH · 2019 to 2023
$1.8M
NIGMS NIH HHS R35 GM131819U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R35GM131819
6 · The paper itself

Abstract

Spatial transcriptomics has enabled the study of mRNA distributions within cells, a key aspect of cellular function. However, there is a dearth of tools that can identify and interpret functionally relevant spatial patterns of subcellular transcript distribution. To address this, we present CellSP, a computational framework for identifying, visualizing, and characterizing consistent subcellular spatial patterns of mRNA. CellSP introduces the concept of "gene-cell modules", which are gene sets with coordinated subcellular transcript distributions in many cells. It provides intuitive visualizations of the captured patterns and offers functional insights into each discovered module. We demonstrate that CellSP reliably identifies functionally significant modules across diverse tissues and technologies. We use the tool to discover subcellular spatial phenomena related to myelination, axonogenesis, and synapse formation in the mouse brain. We find immune response-related modules that change between kidney cancer and healthy samples, and myelination-related modules specific to mouse models of Alzheimer's Disease.

Indexed as

Computational BiologyGene Expression ProfilingSoftwareTranscriptomeAlzheimer DiseaseAnimalsBrainHumansMiceRNA, MessengerRNA, Messenger

Identifiers

PMID41193576
PMCPMC12589652

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.