Statistical challenges for human microbiome analysis

Javier Rivera-Pinto, Carla Estany, Roger Paredes, M. Luz Calle, Marc Noguera-Julián

    Research output: Chapter in BookChapterResearchpeer-review

    Abstract

    © 2017, Springer International Publishing AG. DNA sequencing technologies have revolutionized microbiome studies. In this work we analyze microbiome data from an HIV study focused on the characterization of microbiome composition in HIV-1 infected patients. A 155 cohort of HIV infected and non-infected individuals is analyzed to characterize dietary and gut microbiome association in this group of patients. A penalized Dirichlet Multinomial regression model has been considered. The assumed underlying Dirichlet distribution in this modelization provides additional flexibility to the multinomial model which results in a better fit of the typically overdispersed microbiome data.
    Original languageEnglish
    Title of host publicationTrends in Mathematics
    Pages47-51
    Number of pages4
    Volume7
    ISBN (Electronic)2297-024X
    DOIs
    Publication statusPublished - 1 Jan 2017

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