Seminars “Navigating through ‘omics data: a multivariate perspective”

from March 9, 2020 to March 10, 2020

March 9, 11:00 am & March 10, 10:00 am
Prof Kim-Anh Lê Cao from University of Melbourne will be giving two talks on her work “Navigating through ‘omics data: a multivariate perspective”.

Kim-Anh Lê Cao, University of Melbourne

Prof Kim-Anh Lê Cao from University of Melbourne will be giving two talks on her work “Navigating through ‘omics data: a multivariate perspective”. Both talks will be at IMAG (, salle seminaire 2 in the entrance hall. The first talk will take place on Monday March 9 at 11am and the second will be on Tuesday March 10 at 10am. Abstracts and more details are below.

If you want to meet Kim-Anh outside this schedule, she will be available on Monday afternoon and Tuesday until 2pm. 


Navigating through ‘omics data: a multivariate perspective

A/Prof Kim-Anh Lê Cao

School of Mathematics and Statistics

The University of Melbourne, Australia

Technological improvements have allowed for the collection of data from different molecular compartments (e.g. gene expression, protein abundance) resulting in multiple ‘omics data from the same set of biospecimens or individuals (e.g. transcriptomics, proteomics). We propose to adopt a systems biology holistic approach by statistically integrating data from these multi-omics. Such approach provides improved biological insights compared with traditional single omics analyses, as it allows to take into account interactions between omics layers.

Integrating data include numerous challenges – data are complex and large, each with few samples (< 50) and many molecules (> 10,000), and generated using different technologies. We have developed a comprehensive dimension reduction multivariate framework to address some of these challenges in the R package mixOmics.

Monday March 9 at 11am
In my first talk, I will give a broad overview of the different methods implemented in the package, and how we define statistical data integration in this context. I will then illustrate how we applied these approaches for the analyses of different multi-omics studies, ranging from a human newborns study to multi-omics microbiomes as well as some preliminary work in single cell multi-omics. Across all these studies, our main goal is to identify a signature composed of biological markers of different types to characterise a specific phenotype or disease status, and thus better understand the underlying molecular mechanisms of a biological system.

Tuesday March 10 at 10am
In my second talk, I will present in more detail the multi-omics data integration method DIABLO, a hypothesis-free approach that constructs combinations of variables (e.g. transcripts, proteins, metabolites) that are maximally correlated across data types to identify a minimal subset of markers – a multi-omics signature. This signature can highlight novel findings but is also the starting point to biological network modelling. I will discuss several extensions of this framework to include prior biological knowledge and to identify gene modules, as well as to handle repeated measurements or time-course data.

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 a Career Development Fellowship (CDF1 from the National Health Medical Research Council). 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 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 ( More information about Kim-Anh’s research group:

Published on February 25, 2020

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