Protocol to recover single-cell gene expression profiles from spatial transcriptomics data using cluster computing.

Young Je Lee, Hao Chen, Jose Lugo-Martinez

Abstract read

In one paragraph

Article in STAR protocols, 2025. 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

3 authors.

Young Je LeeRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: youngjel@cs.cmu.edu.

Hao ChenRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Computer Science, University of Illinois Chicago, Chicago, IL 60607, USA. Electronic address: hchen4@andrew.cmu.edu.

Jose Lugo-MartinezRay and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: jlugomar@andrew.cmu.edu.

Funding

TriState SenNET (Lung and Heart) Tissue Map and Atlas consortiumU54AG075931 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TOREN FINKEL, Melanie Koenigshoff · 2021 to 2026

$14.0M

NIA NIH HHS U54 AG075931

6 · The paper itself

Abstract

Many widely used spatial transcriptomics technologies, such as Visium, capture data at multicellular resolution, precluding single-cell analysis. Here, we present scResolve, a computational protocol to recover single-cell gene expression profiles from low-resolution spatial transcriptomics data. We describe steps for computational environment setup and preparing data and formatting. We then detail procedures for running super-resolution inference and cell segmentation modules. scResolve runs in a cluster environment, leveraging parallel computing to accelerate data processing and deliver faster results. For complete details on the use and execution of this protocol, please refer to Chen et al.

Indexed as

Computational BiologyGene Expression ProfilingSingle-Cell AnalysisTranscriptomeCluster AnalysisHumansSoftwarebiotechnology and bioengineeringcomputer sciencesgene expressionsingle cell

Identifiers

PMID39946238

DOI10.1016/j.xpro.2025.103636

PMCPMC11969410

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC

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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.