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Running spell-check to identify regulatory variants

Nature Genetics volume 47, pages 853–855 (2015)Cite this article

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A major challenge in human genetics is pinpointing which non-coding genetic variants affect gene expression and disease risk. A new study in this issue describes a broadly applicable approach for this task that explicitly models cell type–specific regulatory motifs and generates variant effect predictions that are more accurate and interpretable than those of alternative tools.

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Figure 1: Correlation of conservation measures and functional effects with gene expression.

References

  1. Cooper, G.M. & Shendure, J. Nat. Rev. Genet. 12, 628–640 (2011).

    Article  CAS  Google Scholar 

  2. Trynka, G. et al. Nat. Genet. 45, 124–130 (2013).

    Article  CAS  Google Scholar 

  3. Lee, D. et al. Nat. Genet. 47, 955–961 (2015).

    Article  CAS  Google Scholar 

  4. Villar, D. et al. Cell 160, 554–566 (2015).

    Article  CAS  Google Scholar 

  5. Fu, Y. et al. Genome Biol. 15, 480 (2014).

    Article  Google Scholar 

  6. Kircher, M. et al. Nat. Genet. 46, 310–315 (2014).

    Article  CAS  Google Scholar 

  7. Ritchie, G.R., Dunham, I., Zeggini, E. & Flicek, P. Nat. Methods 11, 294–296 (2014).

    Article  CAS  Google Scholar 

  8. Gulko, B., Hubisz, M.J., Gronau, I. & Siepel, A. Nat. Genet. 47, 276–283 (2015).

    Article  CAS  Google Scholar 

  9. Ghandi, M., Lee, D., Mohammad-Noori, M. & Beer, M.A. PLoS Comput. Biol. 10, e1003711 (2014).

    Article  Google Scholar 

  10. Patwardhan, R.P. et al. Nat. Biotechnol. 30, 265–270 (2012).

    Article  CAS  Google Scholar 

  11. Gusev, A. et al. Am. J. Hum. Genet. 95, 535–552 (2014).

    Article  CAS  Google Scholar 

  12. Ma, W. et al. Nat. Methods 12, 71–78 (2015).

    Article  Google Scholar 

  13. Davydov, E.V. et al. PLoS Comput. Biol. 6, e1001025 (2010).

    Article  Google Scholar 

  14. Pollard, K.S., Hubisz, M.J., Rosenbloom, K.R. & Siepel, A. Genome Res. 20, 110–121 (2010).

    Article  CAS  Google Scholar 

  15. Siepel, A. et al. Genome Res. 15, 1034–1050 (2005).

    Article  CAS  Google Scholar 

Download references

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Authors and Affiliations

  1. Martin Kircher and Jay Shendure are in the Department of Genome Sciences, University of Washington, Seattle, Washington, USA.,

    Martin Kircher & Jay Shendure

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  1. Martin Kircher
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  2. Jay Shendure
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Correspondence to Jay Shendure.

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The authors declare no competing financial interests.

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Kircher, M., Shendure, J. Running spell-check to identify regulatory variants. Nat Genet 47, 853–855 (2015). https://doi.org/10.1038/ng.3364

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