Stat-XP: statistics to analyse OMICs data and characterise the exposome

Stat-XP is an introductory short course to statistical models required to analyse high-throughput data from well-established OMICs platforms. This includes genetic, transcriptomic, metabonomics and epigenetics data.

The course will provide an in-depth description of the OMICs data, their features, and the challenges their statistical analysis raises.

Stat-XP will also propose a series of lectures describing the main statistical methods used in molecular epidemiology. These include:

• univariate models and multiple testing correction strategies (FWER, FDR)
• dimension reduction techniques
• variable selection approaches (penalised regression and Bayesian variable selection)

Corresponding seminars will show how these methods are used in practice, and computer-based practical sessions will give the opportunity to use and get familiar with the well-established software/packages enabling such analyses. Finally, we will describe methodological perspectives to improve the analysis of OMICs data in the context of the exposome.

Overview

Stat-XP will enable research professionals to better understand the growing literature relying on the analysis of OMICs data. Participants will be able to run their own analyses at the end of the course.

Contributors

Imperial College London:
Professor Paul Elliott, Professor of Epidemiology and Public Health Medicine, Head of Dept of Epidemiology and Biostatistics.
 Director of MRC-PHE Centre for Environment and Health.
Professor Paolo Vineis,  Professor of Environmental Epidemiology. Dept of Epidemiology and Biostatistics. Adjunct Professor, Columbia University, NYC – USA.
Dr Marc Chadeau-Hyam, Senior Lecturer in Statistical Bioinformatics, Dept of Epidemiology and Biostatistics. Honorary Reader, Utrecht University.
Dr Tim Ebbels,  Reader in Computational Bioinformatics, Dept of Surgery & Cancer .
Dr Gianluca Campanella, Research Fellow, Dept of Epidemiology and Biostatistics.
Dr David Muller, Research Associate, Dept of Epidemiology and Biostatistics.

Utrecht University:
Dr Roel Vermeulen,  Associate Professor, Institute for Risk Assessment Sciences.
Dr Jelle Vlaanderen, Junior Assistant Professor, Institute for Risk Assessment Sciences.

University of Pau et Pays De L'Adour, Queensland University of Technology:
Professor Benoît Liquet, Professor in Statistics, Member of LMAP, Affiliated to ACEMS, Queensland University Technology.

International Agency for Research on Cancer:
Dr Pietro Ferrari, Nutritional Epidemiology Group.
Dr Florence Guida, Post Doctoral Fellow.

Institut National pour la Recherche Medicale (INSERM):
Dr Raphaële Castagné, Research Fellow, Université de Toulouse.