Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr.

Chenxin Flora Jiang, Yuxin Yin, Paul Robson, Yuanhao James Li, Jingyi Jessica Li, Dongyuan Song

Abstract read

In one paragraph

Article in Genome research, 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

6 authors.

Chenxin Flora JiangDepartment of Statistics and Data Science, University of California, Los Angeles, California 90095, USA.ORCID http://orcid.org/0009-0005-7369-4116

Yuxin YinDepartment of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, Connecticut 06030, USA.

Paul RobsonDepartment of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, Connecticut 06030, USA.ORCID http://orcid.org/0000-0002-0191-3958

Yuanhao James LiDepartment of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, Connecticut 06030, USA.

Jingyi Jessica LiDepartment of Statistics and Data Science, University of California, Los Angeles, California 90095, USA; lijy03@fredhutch.org dosong@uchc.edu.ORCID http://orcid.org/0000-0002-9288-5648

Dongyuan SongDepartment of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, Connecticut 06030, USA; lijy03@fredhutch.org dosong@uchc.edu.ORCID http://orcid.org/0000-0003-1114-1215

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial transcriptomics has transformed our ability to explore gene expression within its tissue context, enabling us to dissect subtle yet biologically significant variations

Identifiers

PMID42309667

DOI10.1101/gr.281559.125

PMCPMC13322192

What Socratic holds

Textmetadata

LicenceCC BY-NC

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.