Introduction to genome based analysis of quantitative traits with machine learning and
non-parametric methods
Place: AgroParisTech, Paris (16 rue Claude Bernard)
Key-words: Quantitative genetics, Genomics, Bayesian statistics
Dates: July 2-6, 2012
Registration procedure: Before June 20, send the filled application form via e-mail to:
egsabg@agroparistech
Registration fees (including course notes and material)
 PhD candidates: € 300. Others: € 500.Registration fees have to be paid by bank transfer. Please, note that registration is only
definitive when payment of each invoice has been received.
Aims: The purpose of the course is to provide an updated training on the statistical methods
developed for analyzing genomic data. Special emphasis will be put on Bayesian methods and
variants.
The course is mainly intended to PhD candidates, and is open to young or senior scientists.
Main program:
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Evolution of statistical methods in quantitative genetics.
Challenges from complexity and use of genomic data
Brief review of Bayesian inference; bayesian regression.
Genome-enabled prediction: “genomic BLUP”; the alphabet: bayes A, Bayes B, Bayes C,
Bayes L.
Principles of cross-validation.
The problem of dealing with interactions.
Introduction to non-parametric regression: LOESS, kernel regression, RKHS, radial basis
function, neural networks (NN).
Results from animals and plants.
Additional lectures will be given: Case studies, single-step approaches, approximate Bayesian
computation approach to infer gene regulatory networks, etc.
Level and prerequisites: This course will be taught at an intermediate level. Knowledge of
matrix algebra, linear models and distribution theory is assumed. Knowledge on elementary
Bayesian inference (via a review of Bayesian methods) will be provided in class.
Main lecturer: Daniel Gianola, Professor at the University of Wisconsin-Madison, Animal
Sciences, Dairy Science and Biostatistics and Medical Informatics Departments
Additional lectures will be given by young or senior scientists from INRA (France)
Organizer: Etienne Verrier, Professor, AgroParisTech and INRA-UMR GABI
Language: English