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Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis

Nature Methods volume 13, pages 241244 (2016) | Download Citation

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.

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References

  1. 1.

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

  2. 2.

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

  3. 3.

    et al. PLoS ONE 6, e21208 (2011).

  4. 4.

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

  5. 5.

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

  6. 6.

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

  7. 7.

    et al. Cell 161, 1202–1214 (2015).

  8. 8.

    et al. Cell 161, 1187–1201 (2015).

  9. 9.

    et al. Science 344, 1396–1401 (2014).

  10. 10.

    , & Nat. Methods 11, 637–640 (2014).

  11. 11.

    & Bioinformatics 28, i626–i632 (2012).

  12. 12.

    & J. Mach. Learn. Res. 9, 2579–2605 (2008).

  13. 13.

    et al. Science 343, 776–779 (2014).

  14. 14.

    , , , & Bioinformatics 23, 3251–3253 (2007).

  15. 15.

    , & Development 122, 1165–1174 (1996).

  16. 16.

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

  17. 17.

    et al. J. Neurosci. 32, 16213–16222 (2012).

  18. 18.

    , , , & Proc. Natl. Acad. Sci. USA 108, 15444–15449 (2011).

  19. 19.

    , & Nat. Methods 11, 740–742 (2014).

  20. 20.

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

  21. 21.

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

  22. 22.

    , & Nat. Rev. Neurosci. 7, 883–890 (2006).

  23. 23.

    et al. Nature 445, 168–176 (2007).

  24. 24.

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

  25. 25.

    , , & J. Biol. Chem. 271, 918–924 (1996).

  26. 26.

    , , & PLoS ONE 9, e84460 (2014).

  27. 27.

    , , , & J. Neurosci. 33, 10362–10373 (2013).

  28. 28.

    , , & Science 278, 474–476 (1997).

  29. 29.

    & Nat. Rev. Neurosci. 7, 687–696 (2006).

  30. 30.

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

  31. 31.

    & Genome Biol. 11, R106 (2010).

  32. 32.

    Statistical Methods for Research Workers (Hafner, 1970).

  33. 33.

    Encyclopedia of Environmetrics 2nd edn (Wiley, 2012).

  34. 34.

    , , & Ann. Math. Stat. 18, 413–426 (1974).

  35. 35.

    Publ. Astron. Soc. Pac. 124, 1023 (2012).

  36. 36.

    Ann. Stat. 29, 295–327 (2001).

  37. 37.

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

  38. 38.

    , , , & Nat. Biotechnol. 33, 495–502 (2015).

  39. 39.

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

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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

    • Jian-Bing Fan

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

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

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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.

Competing interests

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

Corresponding author

Correspondence to Peter V Kharchenko.

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    Supplementary Figures 1–5 and Supplementary Notes 1–3

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    Supplementary Software

    Source code: SCDE R Package

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DOI

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

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