Research Summer School 2015

Software and Statistical Methods for Population Genetics (SSMPG 2015)

Aussois, Vanoise national park, September 7th-11st

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Overview 

This is the second edition of the SSMPG summer school. The summer school will start at dinner time on Monday, September 7 and ends at breakfast time on Friday, September 11.

The aim of the summer school is to provide a comprehensive overview on software and statistical methods for detecting genes involved in local adaptation. Lecture notes and software demos will be given during the summer school.

In addition to software demos, we plan to set up a contest to promote learning. Participants will work in groups and will be asked to analyse simulated datasets. The objective will be to find adaptive loci using the different software presented at the summer school.

The summer school will take place in Aussois, a charming, small village in the Vanoise National Park (French Alps). The remote setting, along with the challenging program, were chosen to promote and enhance the communication and interaction between teachers and participants. Lectures and software demos will provide the necessary environment to generate lively discussions and initiate new synergies among the young researchers.

Participants will have the opportunity to present their own research during poster sessions. A detailed program will be provided soon.

Participants should bring their own laptop in order to be able to participate to the contest.

Instructors

Michael Blum, UGA Grenoble (France)
PCAdapt: detecting genes involved in adaptation with principal component-analysis.

Olivier Francois, UGA Grenoble (France)
LEA: An R package for landscape and ecological genome-wide association studies.

Mathieu Gautier, INRA Montpellier (France)
BAYPASS: detecting adaptive loci with and without environmental variables using the covariance matrix.

Katie Lotterhos, Northeastern University (USA)
OutFLANK: a procedure to find Fst outliers based on an inferred distribution of neutral Fst.

Bertrand Servin, INRA Toulouse (France)
hapFLK and FLK tests for the detection of selection signatures based on multiple population genotyping data.

Renaud Vitalis, INRA Montpellier (France)
SELESTIM: Detecting and measuring selection from gene frequency data.


Contact and organization

Michael Blum, CNRS research associate, laboratoire TIMC-IMAG, UGA Grenoble

michael[dot]blum[at]imag[dot]fr

Renaud Vitalis, INRA senior researcher, Centre de Biologie pour la Gestion des Populations, Montpellier

vitalis[at]supagro[dot]inra[dot]fr