Estimating the completeness of large-scale single-cell sequencing projects
Single-cell RNA sequencing is being widely used to catalogue differentiated cell types across tissues, but methods to evaluate how completely these cellular populations have been sampled remain limited. Here, the authors adapt statistical approaches from ecological species-richness estimation to single-cell datasets, developing a framework to assess profiling completeness and showing how it can identify points at which additional sequencing is unlikely to reveal new cellular clusters.
Acknowledgements We thank Henri Pesonen, Leo Lahti, and Yunus Vilkkavaara-Cankocak for their expert comments during the writing of the manuscript. All single-cell data analytics were performed using a computing cluster. The authors acknowledge the CSC—IT Centre for Science, Finland, for providing the computational resources.
MM was supported by the Sakari Alhopuro Foundation. TA was supported by the Norwegian Cancer Society (grants 216104 and 273810), Norwegian Health Authority South-East (grants 2020026 and 2023105), the Radium Hospital Foundation, the Finnish Cancer Foundation, Sigrid Jusélius Foundation, the Research Council of Finland under the frame of EP PerMed (CLL-OUTCOME, grant 367855), and the Research Council of Norway under the frame of EP PerMed (ImmuneT-ME, grant 357095).
During the preparation of this work, the authors used ChatGPT to generate initial code or to shape textual style of the manuscript. After using this tool or service, the authors carefully reviewed and edited the content further as needed and take full responsibility for the content of the publication.
Funding M.M. was supported by the Sakari Alhopuro Foundation and and iCAN—Digital Precision Cancer Medicine Flagship. Y.C. was supported by iCAN—Digital Precision Cancer Medicine Flagship. T.A. was supported by the Norwegian Cancer Society (grants 216104 and 273810), Norwegian Health Authority South-East (grants 2020026 and 2023105), the Radium Hospital Foundation, the Finnish Cancer Foundation, Sigrid Jusélius Foundation, the Research Council of Finland under the frame of EP PerMed (CLL-OUTCOME, grant 367855), iCAN (project: MULTIDRUG) and the Research Council of Norway under the frame of EP PerMed (ImmuneT-ME, grant 357095).
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Author information Author notes These authors contributed equally: Yidian Chu, Sara Vakkilainen. Authors and Affiliations Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland Mitro Miihkinen, Yidian Chu, Sara Vakkilainen, Yevhen Akimov & Tero Aittokallio iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki and Helsinki University Hospital, Helsinki, Finland Mitro Miihkinen, Yidian Chu & Tero Aittokallio Institute for Cancer Research, Department of Cancer Genetics, Oslo University Hospital, Oslo, Norway Tero Aittokallio Oslo Centre for Biostatistics and Epidemiology (OCBE), Faculty of Medicine, University of Oslo, Oslo, Norway Tero Aittokallio Authors Mitro Miihkinen Yidian Chu Sara Vakkilainen Yevhen Akimov Tero Aittokallio Corresponding authors Correspondence to Mitro Miihkinen or Tero Aittokallio .
Ethics declarations Competing interests M.M. and T.A. report research and salary funding from Mobius Biotechnology GmbH. The authors declare no other competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Reprints and permissions About this article Cite this article Miihkinen, M., Chu, Y., Vakkilainen, S. et al. Estimating the completeness of large-scale single-cell sequencing projects. Nat Commun (2026). https://doi.org/10.1038/s41467-026-78221-5 Download citation Received : 25 August 2025 Accepted : 18 September 2026 Published : 08 October 2026 DOI : https://doi.org/10.1038/s41467-026-78221-5
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