By Eran Halperin (UCLA)

High-throughput microbiome analysis has become ubiquitous over the last few years. However, the interpretation of the data is often non-trivial and highly depends on the methodology used for the analysis. I will describe a few methods for the analysis of microbiome in contexts that are typical in such analyses. First, I will describe a new method for microbial source tracking, that is, finding the sources of a microbiome sample. I will demonstrate how using the method one can reach very different conclusions (that make more biological sense) than using previous methods. Specifically, I will show examples on the dynamics of gut microbiome in babies, and on the usage of source tracking as a tool for disease diagnosis. Second, I will discuss novel approaches for the analysis of time-series micorbiome data, and here too, I will show how this new approach results in new biological insights, particularly on the dependence of microbiome in the future on the current composition of the microbiome. The talk will be self contained, and I will not assume any expert knowledge in computer science or statistics.

Location : Auditorium Jaques Monod – MONOD (66) ,Institut Pasteur, Paris

Registration