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Predicting disease variants using biodiversity and machine learning

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An algorithm that uses evolutionary data to predict disease variants makes a case for embracing computational evidence for clinical interpretation of genetic variation.

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Fig. 1: The EVE model predicts human variant pathogenicity using evolutionary information.

References

  1. Frazer, J. et al. Nature 599, 91–95 (2021).

    Article  CAS  Google Scholar 

  2. Landrum, M. J. et al. Nucleic Acids Res. 48, D835–D844 (2020).

    Article  CAS  Google Scholar 

  3. Ng, P. C. & Henikoff, S. Genome Res. 11, 863–874 (2001).

    Article  CAS  Google Scholar 

  4. Reva, B., Antipin, Y. & Sander, C. Nucleic Acids Res. 39, e118 (2011).

    Article  CAS  Google Scholar 

  5. Adzhubei, I., Jordan, D. M. & Sunyaev, S. R. Curr. Protoc. Hum. Genet. 7, 7.20 (2013).

    Google Scholar 

  6. González-Pérez, A. & López-Bigas, N. Am. J. Hum. Genet. 88, 440–449 (2011).

    Article  Google Scholar 

  7. López-Ferrando, V., Gazzo, A., de la Cruz, X., Orozco, M. & Gelpí, J. L. Nucleic Acids Res. 45, W222–W228 (2017).

    Article  Google Scholar 

  8. Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J. & Kircher, M. Nucleic Acids Res. 47, D886–D894 (2019).

    Article  CAS  Google Scholar 

  9. Riesselman, A. J., Ingraham, J. B. & Marks, D. S. Nat. Methods 15, 816–822 (2018).

    Article  CAS  Google Scholar 

  10. Richards, S. et al. Genet. Med. 17, 405–424 (2015).

    Article  Google Scholar 

  11. Karczewski, K. J. et al. Nature 581, 434–443 (2020).

    Article  CAS  Google Scholar 

  12. Martincorena, I. & Campbell, P. J. Science 349, 1483–1489 (2015).

    Article  CAS  Google Scholar 

  13. Muiños, F., Martínez-Jiménez, F., Pich, O., Gonzalez-Perez, A. & Lopez-Bigas, N. Nature 596, 428–432 (2021).

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, Barcelona, Spain

    Claudia Arnedo-Pac, Nuria Lopez-Bigas & Ferran Muiños

  2. Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain

    Nuria Lopez-Bigas

  3. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

    Nuria Lopez-Bigas

Authors
  1. Claudia Arnedo-Pac
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  2. Nuria Lopez-Bigas
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  3. Ferran Muiños
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Corresponding author

Correspondence to Nuria Lopez-Bigas.

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The authors declare no competing interests.

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Arnedo-Pac, C., Lopez-Bigas, N. & Muiños, F. Predicting disease variants using biodiversity and machine learning. Nat Biotechnol 40, 27–28 (2022). https://doi.org/10.1038/s41587-021-01187-w

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  • DOI: https://doi.org/10.1038/s41587-021-01187-w

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