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Predicting functional gene interactions with the hierarchical interaction score

Nature Methods volume 10, pages 1089–1092 (2013)Cite this article

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Abstract

Systems biology aims to unravel the vast network of functional interactions that govern biological systems. To date, the inference of gene interactions from large-scale 'omics data is typically achieved using correlations. We present the hierarchical interaction score (HIS) and show that the HIS outperforms commonly used methods in the inference of functional interactions between genes measured in large-scale experiments, making it a valuable statistic for systems biology.

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Figure 1: Design and properties of the HIS.
Figure 2: HIS performs best in the inference of functional interactions across species.

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Gene Expression Omnibus

References

  1. Moffat, J. & Sabatini, D.M. Nat. Rev. Mol. Cell Biol. 7, 177–187 (2006).

    Article  CAS  Google Scholar 

  2. Tong, A.H. et al. Science 303, 808–813 (2004).

    Article  CAS  Google Scholar 

  3. Costanzo, M. et al. Science 327, 425–431 (2010).

    Article  CAS  Google Scholar 

  4. Nichols, R.J. et al. Cell 144, 143–156 (2011).

    Article  CAS  Google Scholar 

  5. Gavin, A.C. et al. Nature 415, 141–147 (2002).

    Article  CAS  Google Scholar 

  6. Horn, T. et al. Nat. Methods 8, 341–346 (2011).

    Article  CAS  Google Scholar 

  7. Bernards, R. Cell 151, 465–468 (2012).

    Article  CAS  Google Scholar 

  8. Chuang, H.Y., Lee, E., Liu, Y.T., Lee, D. & Ideker, T. Mol. Syst. Biol. 3, 140 (2007).

    Article  Google Scholar 

  9. Lehner, B. J. Exp. Biol. 210, 1559–1566 (2007).

    Article  Google Scholar 

  10. Markowetz, F., Kostka, D., Troyanskaya, O.G. & Spang, R. Bioinformatics 23, i305–i312 (2007).

    Article  CAS  Google Scholar 

  11. Boutros, M., Agaisse, H. & Perrimon, N. Dev. Cell 3, 711–722 (2002).

    Article  CAS  Google Scholar 

  12. Mercer, J. et al. Cell Rep. 2, 1036–1047 (2012).

    Article  CAS  Google Scholar 

  13. Snijder, B. et al. Mol. Syst. Biol. 8, 579 (2012).

    Article  Google Scholar 

  14. Wang, X., Castro, M.A., Mulder, K.W. & Markowetz, F. PLoS Comput. Biol. 8, e1002566 (2012).

    Article  CAS  Google Scholar 

  15. Laufer, C., Fischer, B., Billmann, M., Huber, W. & Boutros, M. Nat. Methods 10, 427–431 (2013).

    Article  CAS  Google Scholar 

  16. Roguev, A. et al. Nat. Methods 10, 432–437 (2013).

    Article  CAS  Google Scholar 

  17. Reshef, D.N. et al. Science 334, 1518–1524 (2011).

    Article  CAS  Google Scholar 

  18. Ravasz, E., Somera, A.L., Mongru, D.A., Oltvai, Z.N. & Barabási, A.-L. Science 29, 1551–1555 (2002).

    Article  Google Scholar 

  19. Ryan, C.J. et al. Mol. Cell 46, 691–704 (2012).

    Article  CAS  Google Scholar 

  20. Schmidt, E.E. et al. Nucleic Acids Res. 41, D1021–D1026 (2013).

    Article  CAS  Google Scholar 

  21. Snijder, B. et al. Nature 461, 520–523 (2009).

    Article  CAS  Google Scholar 

  22. Marbach, D. et al. Nat. Methods 9, 796–804 (2012).

    Article  CAS  Google Scholar 

  23. Huang, D.W. Nat. Protoc. 4, 44–57 (2009).

    Article  CAS  Google Scholar 

  24. Szklarczyk, D. et al. Nucleic Acids Res. 39, D561–D568 (2011).

    Article  CAS  Google Scholar 

  25. Cerami, E.G. et al. Nucleic Acids Res. 39, D685–D690 (2011).

    Article  CAS  Google Scholar 

  26. Steinmetz, L.M. et al. Nat. Genet. 31, 400–404 (2002).

    Article  CAS  Google Scholar 

  27. Jeong, H., Mason, S.P., Barabasi, A.L. & Oltvai, Z.N. Nature 411, 41–42 (2001).

    Article  CAS  Google Scholar 

  28. Butland, G. et al. Nature 433, 531–537 (2005).

    Article  CAS  Google Scholar 

  29. Vinayagam, A. et al. Sci. Signal. 4, rs8 (2011).

    Article  Google Scholar 

  30. Uhlen, M. et al. Nat. Biotechnol. 28, 1248–1250 (2010).

    Article  CAS  Google Scholar 

  31. Barzel, B. & Barabasi, A.L. Nat. Biotechnol. 31, 720–725 (2013).

    Article  CAS  Google Scholar 

  32. Bürckstümmer, T. et al. Nat. Methods doi:10.1038/nmeth.2609 (25 August 2013).10.1038/nmeth.2609

  33. Mali, P. et al. Science 339, 823–826 (2013).

    Article  CAS  Google Scholar 

  34. Sieg, D.J. et al. EMBO J. 17, 5933–5947 (1998).

    Article  CAS  Google Scholar 

  35. Bodenmiller, B., Mueller, L.N., Mueller, M., Domon, B. & Aebersold, R. Nat. Methods 4, 231–237 (2007).

    Article  CAS  Google Scholar 

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Acknowledgements

We would like to acknowledge E.-M. Damm and A. Schmidt for the phosphoproteomics data, A. Patrignani for analysis of the microarray data, Y. Yakimovich for help on the accompanying website, D. Schlaepfer (University of California, San Diego) for the PTK2-rescue cell line, F. Markowetz and X. Wang for help with NEM analysis, and all members of the Pelkmans lab for useful comments on the manuscript. L.P. acknowledges financial support from the SystemsX.ch RTD projects PhosphoNetX and LipidX and the University of Zurich, and B.S. acknowledges financial support from the Swiss National Science Foundation.

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Author notes

  1. Berend Snijder

    Present address: Present address: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.,

Authors and Affiliations

  1. Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

    Berend Snijder, Prisca Liberali, Mathieu Frechin, Thomas Stoeger & Lucas Pelkmans

  2. Systems Biology PhD program, Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland

    Thomas Stoeger

Authors
  1. Berend Snijder
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  2. Prisca Liberali
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  3. Mathieu Frechin
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  5. Lucas Pelkmans
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Contributions

B.S. and L.P. conceived of the study. B.S. developed the method and performed computational analyses. P.L., M.F. and T.S. performed experiments. B.S. and L.P. wrote the manuscript.

Corresponding authors

Correspondence to Berend Snijder or Lucas Pelkmans.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–15 and Supplementary Results (PDF 2162 kb)

Supplementary Table 1

Comparative phosphoproteomics results for PTK2 cell lines (XLSX 381 kb)

Supplementary Table 2

DAVID annotation clustering results for both comparative transcriptomics and phosphoproteomics analysis of PTK2 cell lines (XLSX 506 kb)

Supplementary Software

HIS source code and example (ZIP 1753 kb)

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Snijder, B., Liberali, P., Frechin, M. et al. Predicting functional gene interactions with the hierarchical interaction score. Nat Methods 10, 1089–1092 (2013). https://doi.org/10.1038/nmeth.2655

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