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Regularized Machine Learning in the Genetic Prediction of Complex Traits

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  • Sebastian Okser
  • Tapio Pahikkala
  • Antti Airola
  • Tapio Salakoski
  • Samuli Ripatti
  • Tero Aittokallio

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Suggested Citation

  • Sebastian Okser & Tapio Pahikkala & Antti Airola & Tapio Salakoski & Samuli Ripatti & Tero Aittokallio, 2014. "Regularized Machine Learning in the Genetic Prediction of Complex Traits," PLOS Genetics, Public Library of Science, vol. 10(11), pages 1-9, November.
    • Handle: RePEc:plo:pgen00:1004754
    DOI: 10.1371/journal.pgen.1004754
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    References listed on IDEAS

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    1. Zhi Wei & Kai Wang & Hui-Qi Qu & Haitao Zhang & Jonathan Bradfield & Cecilia Kim & Edward Frackleton & Cuiping Hou & Joseph T Glessner & Rosetta Chiavacci & Charles Stanley & Dimitri Monos & Struan F , 2009. "From Disease Association to Risk Assessment: An Optimistic View from Genome-Wide Association Studies on Type 1 Diabetes," PLOS Genetics, Public Library of Science, vol. 5(10), pages 1-11, October.
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    Cited by:

    1. Laurin Charles & Boomsma Dorret & Lubke Gitta, 2016. "The use of vector bootstrapping to improve variable selection precision in Lasso models," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 15(4), pages 305-320, August.
    2. Brieuc Lehmann & Maxine Mackintosh & Gil McVean & Chris Holmes, 2023. "Optimal strategies for learning multi-ancestry polygenic scores vary across traits," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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