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
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