22 Aug 2019 09:30am to 10:30am

Multivariate microbiome data analysis

Event Location
Conference Room 1
553 St Kilda Road Melbourne Australia
Melbourne VIC 3004
Dr Kim-Anh Le Cao
University of Melbourne, School of Mathematics and Statistics

Our recent breakthroughs and advances in culture independent techniques (whole genome shotgun metagenomics, 16S rRNA amplicon sequencing) have dramatically changed the way we can examine microbial communities. But does the hype of microbiome outweigh 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 microbiome data analysis, and our recent developments to identify microbial signatures using dimension reduction methods. Our methods are implemented in our R toolkit mixOmics dedicated to biological (omics) data integration.


Dr Kim-Anh Lê Cao graduated from her PhD in 2008 at the Université de Toulouse, France.  Soon after her graduation she moved to Australia for her first postdoc at the Institute for Molecular Bioscience, University of Queensland, then was employed as a Research and Consultant Biostatistician at QFAB Bioinformatics. Kim-Anh’s research directions veered towards biomedical problems when she moved to UQ Diamantina Institute in 2014 and was awarded an NHMRC Career Development Fellowship (CDF1). In 2017, she joined the University of Melbourne, at the School of Mathematics and Statistics, and Melbourne Integrative Genomics that hosts biology-focussed researchers with statistical and computational skills. In 2019 she was awarded her NHRMC CDF2, focusing on microbiome studies and received the biennial Moran medal in Statistical Sciences from the Australian Academy of Science.

Dr Kim-Anh Lê Cao is an expert in multivariate statistical methods and develops novel methods for ‘omics data integration. Since 2009, her team has been working on developing the R toolkit mixOmics dedicated to the integrative analysis of `omics' data to help researchers mine and make sense of biological data (http://www.mixOmics.org). More information about Kim-Anh’s research group: http://lecao-lab.science.unimelb.edu.au/