Matthieu Foll

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Identifying loci under natural selection from genomic surveys is of great interest in different research areas. Commonly used methods to separate neutral effects from adaptive effects are based on locus-specific population differentiation coefficients to identify outliers. Here we extend such an approach to estimate directly the probability that each locus(More)
Patterns of genetic diversity between populations are often used to detect loci under selection in genome scans. Indeed, loci involved in local adaptations should show high F(ST) values, whereas loci under balancing selection should rather show low F(ST) values. Most tests of selection based on F(ST) use a null distribution generated under a simple island(More)
The study of population genetic structure is a fundamental problem in population biology because it helps us obtain a deeper understanding of the evolutionary process. One of the issues most assiduously studied in this context is the assessment of the relative importance of environmental factors (geographic distance, language, temperature, altitude, etc.)(More)
We introduce a flexible and robust simulation-based framework to infer demographic parameters from the site frequency spectrum (SFS) computed on large genomic datasets. We show that our composite-likelihood approach allows one to study evolutionary models of arbitrary complexity, which cannot be tackled by other current likelihood-based methods. For simple(More)
MOTIVATION Genetic studies focus on increasingly larger genomic regions of both extant and ancient DNA, and there is a need for simulation software to match these technological advances. We present here a new coalescent-based simulation program fastsimcoal, which is able to quickly simulate a variety of genetic markers scattered over very long genomic(More)
Adaptation to adverse environmental conditions such as high altitude requires physiological and/or morphological changes. Genome scans provide a means to identify the genetic basis of such adaptations without previous knowledge about the particular genetic variants or traits under selection. In this study, we scanned 3027 amplified fragment length(More)
Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular(More)
The spatial structuring of intraspecific genetic diversity is the result of random genetic drift, natural selection, migration, mutation, and their interaction with historical processes. The contribution of each has been typically difficult to estimate, but recent advances in statistical genetics have provided valuable new investigative tools to tackle such(More)
In the last decade, amplified fragment length polymorphisms (AFLPs) have become one of the most widely used molecular markers to study the genetic structure of natural populations. Most of the statistical methods available to study the genetic structure of populations using AFLPs consider these markers as dominant and are thus unable to distinguish between(More)
SUMMARY SPLATCHE2 is a program to simulate the demography of populations and the resulting molecular diversity for a wide range of evolutionary scenarios. The spatially explicit simulation framework can account for environmental heterogeneity and fluctuations, and it can manage multiple population sources. A coalescent-based approach is used to generate(More)