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The Phylogenetic LASSO and the Microbiome: Metagenomic modeling in fecal microbiota transplantation

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dc.contributor.advisor Kim, Peter
dc.contributor.advisor Pereira, Rajesh Rush, Stephen Thomas Anthony 2017-03-21T16:54:08Z 2017-03-21T16:54:08Z 2017-12 2017-02-08 2017-03-21
dc.description.abstract Scientific investigations that incorporate next generation sequencing involve analyses of high-dimensional data where the need to organize, collate and interpret the outcomes are pressingly important. Data of the microbiome can currently be collected, leading to possible advances in personalized medicine. In this thesis, we lay down a statistical framework for incorporating metagenomic information in predictive modeling with a view toward synthesis of products tailored to individual patients. In particular, we develop the phylogenetic LASSO ($\Phi$-LASSO), a form of model regularization which incorporates known relationships between predictors for the purpose of model selection. We apply the $\Phi$-LASSO to a pilot metagenomic study on the efficacy of fecal microbiota transplantation in the treatment of {\it Clostridium difficile} infections. Although the thesis applies the technique to data for a particular infectious disease, the methodology is sufficiently rich to be expanded to other problems in medicine, especially those in which coincident `-omics' covariates and clinical responses are simultaneously captured. en_US
dc.description.sponsorship NSERC CIHR en_US
dc.language.iso en en_US
dc.rights Attribution-NoDerivs 2.5 Canada *
dc.rights.uri *
dc.subject statistics en_US
dc.subject metagenomics en_US
dc.subject regularized regression en_US
dc.subject classification en_US
dc.subject high dimensional data analysis en_US
dc.subject oracle property en_US
dc.subject sparsity en_US
dc.subject Clostridium difficile en_US
dc.subject personalized medicine en_US
dc.subject model selection en_US
dc.title The Phylogenetic LASSO and the Microbiome: Metagenomic modeling in fecal microbiota transplantation en_US
dc.type Thesis en_US Mathematics and Statistics en_US Doctor of Philosophy en_US Department of Mathematics and Statistics en_US
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Attribution-NoDerivs 2.5 Canada Except where otherwise noted, this item's license is described as Attribution-NoDerivs 2.5 Canada