Challenges in microbiome data analysis

Our recent breakthroughs and advances in culture independent techniques, such as shotgun metagenomics and 16S rRNA amplicon sequencing have dramatically changed the way we can examine microbial communities. But does the hype of microbiome outweighs the potential of our understanding of this ‘second genome’? There are many hurdles to tackle before we are able to identify and compare bacteria driving changes in their ecosystem. In addition to the bioinformatics challenges, current statistical methods are limited to make sense of these complex data that are inherently sparse, compositional and multivariate. I will discuss some of the topical challenges in 16S data analysis, including the presence of confounding variables and batch effects, some experimental design considerations, and share my own personal story on how a team of rogue statisticians conducted their own mice microbiome experiment leading to somewhat surprising results! I will also present our latest analyses to identify multivariate microbial signatures in immune-mediated diseases and discuss what are the next analytical challenges I envision. This presentation will combine the results of exciting and highly collaborative works between a team of eager data analysts, immunologists and microbiologists. For once, the speaker will abstain from talking about data integration, or mixOmics (oops! but if you are interested keep an eye out in PLOS Comp Biol).