Deterministic patterns in single-cell transcriptomic data.

Zhixing Cao, Yiling Wang, Ramon Grima

Abstract read

In one paragraph

Article in NPJ systems biology and applications, 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.

Zhixing CaoState Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China. z.cao@queensu.ca.

Yiling WangState Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China.

Ramon GrimaSchool of Biological Sciences, University of Edinburgh, Edinburgh, UK. ramon.grima@ed.ac.uk.

Funding

Leverhulme Trust RPG-2020- 327Natural Sciences and Engineering Research Council of Canada RGPIN-2024-06015NSFC 62073137

6 · The paper itself

Abstract

We report the existence of deterministic patterns in statistical plots of single-cell transcriptomic data. We develop a theory showing that the patterns are neither artifacts introduced by the measurement process nor due to underlying biological mechanisms. Rather they naturally emerge from finite sample size effects. The theory precisely predicts the patterns in data from multiplexed error-robust fluorescence in situ hybridization and five different types of single-cell sequencing platforms.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisTranscriptomeAlgorithmsComputational BiologyHumansIn Situ Hybridization, Fluorescence

Identifiers

PMID39799124

DOI10.1038/s41540-025-00490-5

PMCPMC11724867

What OpenQuestion holds

Textmetadata

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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.