Nasal DNA methylation at three CpG sites predicts childhood allergic disease
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DOI: 10.1038/s41467-022-35088-6
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- Takaya Saito & Marc Rehmsmeier, 2015. "The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
- Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
- Andres Cardenas & Joanne E. Sordillo & Sheryl L. Rifas-Shiman & Wonil Chung & Liming Liang & Brent A. Coull & Marie-France Hivert & Peggy S. Lai & Erick Forno & Juan C. Celedón & Augusto A. Litonjua &, 2019. "The nasal methylome as a biomarker of asthma and airway inflammation in children," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
- January Weiner & Jeroen Maertzdorf & Jayne S. Sutherland & Fergal J. Duffy & Ethan Thompson & Sara Suliman & Gayle McEwen & Bonnie Thiel & Shreemanta K. Parida & Joanna Zyla & Willem A. Hanekom & Robe, 2018. "Metabolite changes in blood predict the onset of tuberculosis," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Tingley, Dustin & Yamamoto, Teppei & Hirose, Kentaro & Keele, Luke & Imai, Kosuke, 2014. "mediation: R Package for Causal Mediation Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i05).
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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- Zhaozhong Zhu & Yijun Li & Robert J. Freishtat & Juan C. Celedón & Janice A. Espinola & Brennan Harmon & Andrea Hahn & Carlos A. Camargo & Liming Liang & Kohei Hasegawa, 2023. "Epigenome-wide association analysis of infant bronchiolitis severity: a multicenter prospective cohort study," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
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