SMS scnews item created by John Ormerod at Fri 29 Sep 2017 2303
Type: Seminar
Distribution: World
Expiry: 6 Oct 2017
Calendar1: 6 Oct 2017 1400-1500
CalLoc1: Carslaw 173
CalTitle1: Challenges in microbiome data analysis (also known as "poop analyses")
Auth: (jormerod) in SMS-WASM

Statistics Seminar: Kim-Anh Le Cao (University of Melbourne) -- Challenges in microbiome data analysis (also known as "poop analyses")


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). 

Dr Kim-Anh Lê Cao (NHMRC career development fellow, Senior Lecturer) recently 
joined the University of Melbourne (Centre for Systems Genomics and School of 
Mathematics and Statistics). She was awarded her PhD from the Université de 
Toulouse, France and moved Australia as a postdoctoral research fellow at the 
Institute for Molecular Bioscience, University of Queensland. She was hired as 
a research and consultant at QFAB Bioinformatics where she developed a 
multidisciplinary approach to her research. Between 2014 - 2017 she led a 
computational biostatistics group at the biomedical research UQ Diamantina 
Institute. Dr Kim-Anh Lê Cao is an expert in multivariate statistical methods 
and novel developments. Since 2009, her team has been working on implementing 
the R toolkit mixOmics dedicated to the integrative analysis of `omics’ data 
to help researchers mine and make sense of biological data 

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