Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Matters Arising
  • Published:

Reply to: False positives in study of memory-related gene expression

Nature volume 642, pages E4–E6 (2025)Cite this article

The Original Article was published on 04 June 2025

replying to: E. A. Mukamel & Z. Yu. Nature https://doi.org/10.1038/s41586-025-08988-y (2025).

In the accompanying Comment1, Mukamel and Yu propose that the statistical analysis in our Article2 is misguided. However, as explained below, Mukamel and Yu unfortunately misunderstood our methodology, both in the details of the statistical analysis and in the purpose of the experiments. Moreover, they have taken a narrow and extreme position regarding the use of statistics that does not reflect established expert opinion in the field.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Reanalysis of engram genes in BLA.Int.Gpr88 neurons.

Data availability

Transcriptomics data described in the manuscript have been deposited at the Gene Expression Omnibus (GEO) under accession GSE246147.

References

  1. Mukamel, E. A. & Yu, Z. Nature https://doi.org/10.1038/s41586-025-08988-y (2025).

  2. Sun, W. et al. Spatial transcriptomics reveal neuron–astrocyte synergy in long-term memory. Nature 627, 374–381 (2024).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  3. Rothman, K. J. No adjustments are needed for multiple comparisons. Epidemiology 1, 43–46 (1990).

    Article  PubMed  CAS  Google Scholar 

  4. Saville, D. J. Multiple comparison procedures: the practical solution. Am. Stat. 44, 174–180 (1990).

    Article  Google Scholar 

  5. Heumos, L. et al. Best practices for single-cell analysis across modalities. Nat. Rev. Genet. 24, 550–572 (2023).

    Article  PubMed  CAS  Google Scholar 

  6. Wang, B. et al. Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection. Nat Microbiol 8, 1846–1862 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Wang, F. et al. Single-cell and spatial transcriptome analysis reveals the cellular heterogeneity of liver metastatic colorectal cancer. Sci. Adv. 9, eadf5464 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Yeo, A. T. et al. Single-cell RNA sequencing reveals evolution of immune landscape during glioblastoma progression. Nat. Immunol. 23, 971–984 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Ma, Y. et al. Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies. Nat. Commun. 11, 1585 (2020).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  10. McFarland, J. M. et al. Multiplexed single-cell transcriptional response profiling to define cancer vulnerabilities and therapeutic mechanism of action. Nat. Commun. 11, 4296 (2020).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  11. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).

    Article  MathSciNet  Google Scholar 

  12. Hrvatin, S. et al. Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex. Nat. Neurosci. 21, 120–129 (2018).

    Article  PubMed  CAS  Google Scholar 

  13. Bhattacherjee, A. et al. Cell type-specific transcriptional programs in mouse prefrontal cortex during adolescence and addiction. Nat. Commun. 10, 4169 (2019).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  14. Kunes, R. Z., Walle, T., Land, M., Nawy, T. & Pe’er, D. Supervised discovery of interpretable gene programs from single-cell data. Nat. Biotechnol. 42, 1084–1095 (2024).

    Article  PubMed  CAS  Google Scholar 

  15. Squair, J. W. et al. Confronting false discoveries in single-cell differential expression. Nat. Commun. 12, 5692 (2021).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Wenfei Sun, Michelle B. Chen & Stephen R. Quake

  2. Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA

    Wenfei Sun, Zhihui Liu, Xian Jiang & Thomas C. Südhof

  3. Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA, USA

    Zhihui Liu & Thomas C. Südhof

  4. Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Hua Dong

  5. Chan Zuckerberg Initiative, Redwood City, CA, USA

    Jonathan Liu & Stephen R. Quake

Authors
  1. Wenfei Sun
    View author publications

    Search author on:PubMed Google Scholar

  2. Zhihui Liu
    View author publications

    Search author on:PubMed Google Scholar

  3. Xian Jiang
    View author publications

    Search author on:PubMed Google Scholar

  4. Michelle B. Chen
    View author publications

    Search author on:PubMed Google Scholar

  5. Hua Dong
    View author publications

    Search author on:PubMed Google Scholar

  6. Jonathan Liu
    View author publications

    Search author on:PubMed Google Scholar

  7. Thomas C. Südhof
    View author publications

    Search author on:PubMed Google Scholar

  8. Stephen R. Quake
    View author publications

    Search author on:PubMed Google Scholar

Contributions

W.S. performed bioinformatic analyses under supervision of S.R.Q. and T.C.S. W.S., S.R.Q. and T.C.S. wrote the manuscript. Z.L., X.J., M.B.C., H.D. and J.L. reviewed and edited the manuscript.

Corresponding authors

Correspondence to Thomas C. Südhof or Stephen R. Quake.

Ethics declarations

Competing interests

The authors declare no competing interests

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

DEGs for Gpr88 engram.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, W., Liu, Z., Jiang, X. et al. Reply to: False positives in study of memory-related gene expression. Nature 642, E4–E6 (2025). https://doi.org/10.1038/s41586-025-08989-x

Download citation

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41586-025-08989-x

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing