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.

  • Brief Communication
  • Published:

Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis

Nature Methods volume 13, pages 241–244 (2016)Cite this article

Subjects

Abstract

The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However, identifying such aspects from noisy single-cell RNA-seq data remains challenging. We developed pathway and gene set overdispersion analysis (PAGODA) to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.

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

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Figure 1: Overview of PAGODA.
Figure 2: PAGODA analysis of data from 3,005 mouse cortical and hippocampal cells5.
Figure 3: Transcriptional heterogeneity of 65 NPCs in embryonic mouse cortex.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Referenced accessions

Gene Expression Omnibus

References

  1. Islam, S. et al. Nat. Methods 11, 163–166 (2014).

    Article  CAS  PubMed  Google Scholar 

  2. Picelli, S. et al. Nat. Methods 10, 1096–1098 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. Tang, F. et al. PLoS ONE 6, e21208 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Usoskin, D. et al. Nat. Neurosci. 18, 145–153 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Zeisel, A. et al. Science 347, 1138–1142 (2015).

    Article  CAS  PubMed  Google Scholar 

  6. Buettner, F. et al. Nat. Biotechnol. 33, 155–160 (2015).

    Article  CAS  PubMed  Google Scholar 

  7. Macosko, E.Z. et al. Cell 161, 1202–1214 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Klein, A.M. et al. Cell 161, 1187–1201 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Patel, A.P. et al. Science 344, 1396–1401 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Grün, D., Kester, L. & van Oudenaarden, A. Nat. Methods 11, 637–640 (2014).

    Article  PubMed  Google Scholar 

  11. Buettner, F. & Theis, F.J. Bioinformatics 28, i626–i632 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. van der Maaten, L.J.P. & Hinton, G.E. J. Mach. Learn. Res. 9, 2579–2605 (2008).

    Google Scholar 

  13. Jaitin, D.A. et al. Science 343, 776–779 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Subramanian, A., Kuehn, H., Gould, J., Tamayo, P. & Mesirov, J.P. Bioinformatics 23, 3251–3253 (2007).

    Article  CAS  PubMed  Google Scholar 

  15. Blaschke, A.J., Staley, K. & Chun, J. Development 122, 1165–1174 (1996).

    CAS  PubMed  Google Scholar 

  16. Rehen, S.K. et al. Proc. Natl. Acad. Sci. USA 98, 13361–13366 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Peterson, S.E. et al. J. Neurosci. 32, 16213–16222 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Herr, K.J., Herr, D.R., Lee, C.W., Noguchi, K. & Chun, J. Proc. Natl. Acad. Sci. USA 108, 15444–15449 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kharchenko, P.V., Silberstein, L. & Scadden, D.T. Nat. Methods 11, 740–742 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Pollen, A.A. et al. Nat. Biotechnol. 32, 1053–1058 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Kawaguchi, A. et al. Development 135, 3113–3124 (2008).

    Article  CAS  PubMed  Google Scholar 

  22. Kriegstein, A., Noctor, S. & Martinez-Cerdeno, V. Nat. Rev. Neurosci. 7, 883–890 (2006).

    Article  CAS  PubMed  Google Scholar 

  23. Lein, E.S. et al. Nature 445, 168–176 (2007).

    Article  CAS  PubMed  Google Scholar 

  24. Englund, C. et al. J. Neurosci. 25, 247–251 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Uetsuki, T., Takagi, K., Sugiura, H. & Yoshikawa, K. J. Biol. Chem. 271, 918–924 (1996).

    Article  CAS  PubMed  Google Scholar 

  26. Minamide, R., Fujiwara, K., Hasegawa, K. & Yoshikawa, K. PLoS ONE 9, e84460 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Huang, Z., Fujiwara, K., Minamide, R., Hasegawa, K. & Yoshikawa, K. J. Neurosci. 33, 10362–10373 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Anderson, S.A., Eisenstat, D.D., Shi, L. & Rubenstein, J.L. Science 278, 474–476 (1997).

    Article  CAS  PubMed  Google Scholar 

  29. Wonders, C.P. & Anderson, S.A. Nat. Rev. Neurosci. 7, 687–696 (2006).

    Article  CAS  PubMed  Google Scholar 

  30. Ma, T. et al. Cereb. Cortex 22, 2120–2130 (2012).

    Article  PubMed  Google Scholar 

  31. Anders, S. & Huber, W. Genome Biol. 11, R106 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Fisher, R.A. Statistical Methods for Research Workers (Hafner, 1970).

  33. Abdel, H.E. Encyclopedia of Environmetrics 2nd edn (Wiley, 2012).

  34. Hasings, C., Mosteller, F., Tukey, J.W. & Winsor, C.P. Ann. Math. Stat. 18, 413–426 (1974).

    Article  Google Scholar 

  35. Bailey, S. Publ. Astron. Soc. Pac. 124, 1023 (2012).

    Article  Google Scholar 

  36. Johnstone, I.M. Ann. Stat. 29, 295–327 (2001).

    Article  Google Scholar 

  37. Benjamini, Y. & Hochberg, Y. J. R. Stat. Soc. Series B Stat. Methodol. 57, 289–300 (1995).

    Google Scholar 

  38. Satija, R., Farrell, J.A., Gennert, D., Schier, A.F. & Regev, A. Nat. Biotechnol. 33, 495–502 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Achim, K. et al. Nat. Biotechnol. 33, 503–509 (2015).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank D. Usoskin, P. Ernfors and S. Linnarsson for helpful comments on the analysis approach. This work was supported by an Ellison Medical Foundation award and a US National Science Foundation (NSF) CAREER award (NSF-14-532) to P.V.K., an NSF graduate research fellowship (DGE1144152) to J.F., and US National Institutes of Health (NIH) grants U01 MH098977 (to K.Z. and J.C.) and NIH R01 NS084398 (to J.C.). G.E.K. was supported by NIH grant T32 AG00216.

Author information

Author notes

  1. Jian-Bing Fan

    Present address: Present address: AnchorDx Corporation, International Biotech Island, Guangzhou, Guangdong, China.,

Authors and Affiliations

  1. Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA

    Jean Fan, Joseph L Herman & Peter V Kharchenko

  2. Illumina Inc., San Diego, California, USA

    Neeraj Salathia, Fiona Kaper & Jian-Bing Fan

  3. Department of Bioengineering, University of California, San Diego, California, USA

    Rui Liu & Kun Zhang

  4. Department of Molecular and Cellular Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, California, USA

    Gwendolyn E Kaeser, Yun C Yung & Jerold Chun

  5. Harvard Stem Cell Institute, Cambridge, Massachusetts, USA.,

    Peter V Kharchenko

Authors
  1. Jean Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neeraj Salathia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rui Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gwendolyn E Kaeser
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yun C Yung
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Joseph L Herman
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Fiona Kaper
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jian-Bing Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Kun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jerold Chun
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Peter V Kharchenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.Z., J.C. and P.V.K. conceived the study. N.S., R.L., G.E.K., Y.C.Y., F.K. and J.-B.F. carried out the single-cell purification and RNA-seq measurements. G.E.K. and J.C. carried out RNAscope in situ validation. J.F. and P.V.K. designed and implemented the statistical analysis approach, with the help of J.L.H. P.V.K. and J.F. wrote the manuscript with the help of J.C. and K.Z.

Corresponding author

Correspondence to Peter V Kharchenko.

Ethics declarations

Competing interests

N.S. and F.K. are a current employees and shareholders of Illumina, Inc.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Notes 1–3 (PDF 9354 kb)

Supplementary Software

Source code: SCDE R Package (ZIP 1862 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, J., Salathia, N., Liu, R. et al. Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis. Nat Methods 13, 241–244 (2016). https://doi.org/10.1038/nmeth.3734

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.3734

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
pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy