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Feature Selection in metabolomics with PLS-derived methods

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  • Martin, Manon
  • Govaerts, Bernadette

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  • Martin, Manon & Govaerts, Bernadette, 2019. "Feature Selection in metabolomics with PLS-derived methods," LIDAM Discussion Papers ISBA 2019020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvad:2019020
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    References listed on IDEAS

    as
    1. Feraud, Baptiste & Munaut, Carine & Martin, Manon & Verleysen, Michel & Govaerts, Bernadette, 2017. "Combining strong sparsity and competitive predictive power with the L-sOPLS approach for biomarker discovery in metabolomics," LIDAM Reprints ISBA 2017045, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Prasad Naik & Chih‐Ling Tsai, 2000. "Partial least squares estimator for single‐index models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 763-771.
    3. Marine Jeanmougin & Aurelien de Reynies & Laetitia Marisa & Caroline Paccard & Gregory Nuel & Mickael Guedj, 2010. "Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-9, September.
    4. Florian Rohart & Benoît Gautier & Amrit Singh & Kim-Anh Lê Cao, 2017. "mixOmics: An R package for ‘omics feature selection and multiple data integration," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-19, November.
    5. Feraud, Baptiste & Munaut, Carine & Martin, Manon & Verleysen, Michel & Govaerts, Bernadette, 2017. "Combining strong sparsity and competitive predictive power with the L-sOPLS approach for biomarker discovery in metabolomics," LIDAM Discussion Papers ISBA 2017020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Hyonho Chun & Sündüz Keleş, 2010. "Sparse partial least squares regression for simultaneous dimension reduction and variable selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 3-25, January.
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