Evidence map›Paper›PMID 41630030›Full record

ArticleGenome biology2026

smoppix: unified nonparametric analysis of single-molecule spatial omics data using probabilistic indices.

Stijn Hawinkel, Xilan Yang, Ward Poelmans, Hans Motte, Tom Beeckman, Steven Maere

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PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 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

6 authors.

Stijn HawinkelDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Xilan YangDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Ward PoelmansDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Hans MotteDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Tom BeeckmanDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.
Steven MaereDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium. steven.maere@psb.vib-ugent.be.

Funding

Agentschap Innoveren en Ondernemen HBC.2019.2814Fonds Wetenschappelijk Onderzoek 11I3721NFonds Wetenschappelijk Onderzoek 1282825NFonds Wetenschappelijk Onderzoek G027313N
6 · The paper itself

Abstract

Spatial omics technologies localize individual molecules at subcellular resolution, yet growing numbers of molecules, features and replicates set analysis challenges. We present smoppix, a nonparametric analysis method based on the probabilistic index, to test for several uni- and bivariate localization patterns. It exploits the high-dimensionality of the data for variance weighting and for providing a background null distribution, unique for every molecule. Moreover, smoppix sidesteps segmentation, edge correction, warping and density estimation, and is scalable thanks to an exact permutation null distribution. We unearth spatial patterns in datasets from four kingdoms, and validate some findings experimentally on spikemoss roots.

Indexed as

GenomicsSingle Molecule ImagingAlgorithms

Identifiers

PMID41630030
PMCPMC12951914

What OpenQuestion holds

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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.