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Interactive analysis and assessment of single-cell copy-number variations


We present Ginkgo (, a user-friendly, open-source web platform for the analysis of single-cell copy-number variations (CNVs). Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells. We validated Ginkgo by reproducing the results of five major studies. After comparing three commonly used single-cell amplification techniques, we concluded that degenerate oligonucleotide-primed PCR is the most consistent for CNV analysis.

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Figure 1: Flowchart for performing single-cell copy-number analysis with Ginkgo.
Figure 2: Assessment of data quality for different single-cell whole genome amplification methods using Ginkgo.

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  1. Shapiro, E., Biezuner, T. & Linnarsson, S. Nat. Rev. Genet. 14, 618–630 (2013).

    Article  CAS  Google Scholar 

  2. Wigler, M. Genome Med 4, 79 (2012).

    Article  Google Scholar 

  3. McConnell, M.J. et al. Science 342, 632–637 (2013).

    Article  CAS  Google Scholar 

  4. Blainey, P.C. FEMS Microbiol. Rev. 37, 407–427 (2013).

    Article  CAS  Google Scholar 

  5. Wang, J., Fan, H.C., Behr, B. & Quake, S.R. Cell 150, 402–412 (2012).

    Article  CAS  Google Scholar 

  6. Gundry, M., Li, W., Maqbool, S.B. & Vijg, J. Nucleic Acids Res. 40, 2032–2040 (2012).

    Article  CAS  Google Scholar 

  7. Navin, N. et al. Nature 472, 90–94 (2011).

    Article  CAS  Google Scholar 

  8. Ni, X. et al. Proc. Natl. Acad. Sci. USA 110, 21083–21088 (2013).

    Article  CAS  Google Scholar 

  9. Lu, S. et al. Science 338, 1627–1630 (2012).

    Article  CAS  Google Scholar 

  10. Navin, N. et al. Genome Res. 20, 68–80 (2010).

    Article  CAS  Google Scholar 

  11. Henrichsen, C.N., Chaignat, E. & Reymond, A. Hum. Mol. Genet. 18, R1–R8 (2009).

    Article  CAS  Google Scholar 

  12. Alkan, C., Coe, B.P. & Eichler, E.E. Nat. Rev. Genet. 12, 363–376 (2011).

    Article  CAS  Google Scholar 

  13. Baslan, T. et al. Nat. Protoc. 7, 1024–1041 (2012).

    Article  CAS  Google Scholar 

  14. Smits, S.A. & Ouverney, C.C. PLoS One 5, e12267 (2010).

    Article  Google Scholar 

  15. Zong, C., Lu, S., Chapman, A.R. & Xie, X.S. Science 338, 1622–1626 (2012).

    Article  CAS  Google Scholar 

  16. Hou, Y. et al. Cell 155, 1492–1506 (2013).

    Article  CAS  Google Scholar 

  17. Ross, M.G. et al. Genome Biol. 14, R51 (2013).

    Article  Google Scholar 

  18. Navin, N.E. Genome Biol. 15, 452 (2014).

    Article  Google Scholar 

  19. Cai, X. et al. Cell Rep. 8, 1280–1289 (2014).

    Article  CAS  Google Scholar 

  20. Chen, M. et al. PLoS One 9, e114520 (2014).

    Article  Google Scholar 

  21. de Bourcy, C.F. et al. PLoS One 9, e105585 (2014).

    Article  Google Scholar 

  22. Evrony, G.D. et al. Cell 151, 483–496 (2012).

    Article  CAS  Google Scholar 

  23. Kirkness, E.F. et al. Genome Res. 23, 826–832 (2013).

    Article  CAS  Google Scholar 

  24. Langmead, B. et al. Genome Biol. 10, R25 (2009).

    Article  Google Scholar 

  25. Baslan, T. et al. Genome Res. 25, 714–724 (2015).

    Article  CAS  Google Scholar 

  26. Cleveland, W.S. Am. Stat. 35, 54 (1981).

    Article  Google Scholar 

  27. Olshen, A.B. et al. Biostatistics 5, 557–572 (2004).

    Article  Google Scholar 

  28. Daley, T. & Smith, A.D. Bioinformatics 30, 3159–3165 (2014).

    Article  CAS  Google Scholar 

  29. Abyzov, A. et al. Genome Res. 21, 974–984 (2011).

    Article  CAS  Google Scholar 

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We thank N. Navin and P. Andrews for their helpful discussions and for assisting with data access. The project was supported in part by the US National Institutes of Health (award R01-HG006677 to M.C.S.), the US National Science Foundation (DBI-1350041 to M.C.S.), the Starr Cancer Consortium (I7-A723 to G.S.A.), the Breast Cancer Research Foundation (BCRF) (to M.W. and J.H.), the Simons Foundation, Simons Center for Quantitative Biology (SFARI award number 235988 to M.W.), the Susan G. Komen Foundation (llR13265578 to J.H.), the Prostate Cancer Foundation (Challenge Award to J.H.), the Cold Spring Harbor Laboratory (CSHL) Cancer Center (Support Grant 5P30CA045508) and the Watson School of Biological Sciences at CSHL through a training grant (5T32GM065094) from the US National Institutes of Health.

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Authors and Affiliations



T.G. and R.A. developed the software and conducted the computational experiments. M.C.S., M.W., J.H. and G.S.A. designed the experiments. T.B. and J.K. assisted with the analysis and helped design the experiments. All of the authors wrote and edited the manuscript. All of the authors read and approved the final manuscript.

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Correspondence to Michael C Schatz.

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The authors declare no competing financial interests.

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Supplementary Text and Figures

Supplementary Figures 1–13, Supplementary Tables 1–3 and Supplementary Note (PDF 2362 kb)

Supplementary Software

Gingko software (ZIP 6669 kb)

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Garvin, T., Aboukhalil, R., Kendall, J. et al. Interactive analysis and assessment of single-cell copy-number variations. Nat Methods 12, 1058–1060 (2015).

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