The Florence Center for Data Science is happy to present the “Data Science Christmas Lecture” which is going to be held by Marina Vannucci, Noah Harding Professor of Statistics, Rice University 

When: 16th December 2021, from 3 to 4.30 pm

Where:  Aula 205 (ex 32) – DISIA – Viale Morgagni 59. The participation on site is restricted and you need to register here https://labdisia.disia.unifi.it/reserve205/. 

               If you decide to attend the event, after registering please send us an email at this email address datascience@unifi.it  

               The Lecture will be available also online. Please register here to participate https://us02web.zoom.us/webinar/register/WN_0QB9L_b3RlS9Zp5Rix30_g

Speaker: Marina Vannucci – Noah Harding Professor of Statistics, Rice University

Title: Bayesian Models for Microbiome Data with Variable Selection

Abstract: I will describe Bayesian models developed for understanding how the microbiome varies within a population of interest. I will focus on integrative analyses, where the goal is to combine microbiome data with other available information (e.g. dietary patterns) to identify significant associations between taxa and a set of predictors. For this, I will describe a general class of hierarchical Dirichlet-Multinomial (DM) regression models which use spike-and-slab priors for the selection of the significant associations. I will also describe a joint model that efficiently embeds DM regression models and compositional regression frameworks, in order to investigate how the microbiome may affect the relation between dietary factors and phenotypic responses, such as body mass index. I will discuss the advantages and limitations of the proposed methods with respect to current standard approaches used in the microbiome community and will present results on the analysis of real datasets. If time allows, I will also briefly present extensions of the model to mediation analysis.