Deterministic patterns in single-cell transcriptomic data

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...

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Main Authors: Zhixing Cao, Yiling Wang, Ramon Grima
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Systems Biology and Applications
Online Access:https://doi.org/10.1038/s41540-025-00490-5
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author Zhixing Cao
Yiling Wang
Ramon Grima
author_facet Zhixing Cao
Yiling Wang
Ramon Grima
author_sort Zhixing Cao
collection DOAJ
description 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.
format Article
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institution Kabale University
issn 2056-7189
language English
publishDate 2025-01-01
publisher Nature Portfolio
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series npj Systems Biology and Applications
spelling doaj-art-985556d7e0e944ffb876898407158d452025-01-12T12:28:51ZengNature Portfolionpj Systems Biology and Applications2056-71892025-01-011111510.1038/s41540-025-00490-5Deterministic patterns in single-cell transcriptomic dataZhixing Cao0Yiling Wang1Ramon Grima2State Key Laboratory of Bioreactor Engineering, East China University of Science and TechnologyState Key Laboratory of Bioreactor Engineering, East China University of Science and TechnologySchool of Biological Sciences, University of EdinburghAbstract 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.https://doi.org/10.1038/s41540-025-00490-5
spellingShingle Zhixing Cao
Yiling Wang
Ramon Grima
Deterministic patterns in single-cell transcriptomic data
npj Systems Biology and Applications
title Deterministic patterns in single-cell transcriptomic data
title_full Deterministic patterns in single-cell transcriptomic data
title_fullStr Deterministic patterns in single-cell transcriptomic data
title_full_unstemmed Deterministic patterns in single-cell transcriptomic data
title_short Deterministic patterns in single-cell transcriptomic data
title_sort deterministic patterns in single cell transcriptomic data
url https://doi.org/10.1038/s41540-025-00490-5
work_keys_str_mv AT zhixingcao deterministicpatternsinsinglecelltranscriptomicdata
AT yilingwang deterministicpatternsinsinglecelltranscriptomicdata
AT ramongrima deterministicpatternsinsinglecelltranscriptomicdata