BayeScan aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. BayeScan is based on the multinomial-Dirichlet model. One of the simplest possible scenarios covered consists of an island model in which subpopulation allele frequencies are correlated through a common migrant gene pool from which they differ in varying degrees. The difference in allele frequency between this common gene pool and each subpopulation is measured by a subpopulation specific FST coefficient. Therefore, this formulation can consider realistic ecological scenarios where the effective size and the immigration rate may differ among subpopulations.
- HPC_BAYESCAN_DIR - installation directory
If you publish research that uses bayescan you have to cite it as follows:
Foll M and OE Gaggiotti (2008) A genome scan method to identify selected loci appropriate for both dominant and codominant markers: A Bayesian perspective. Genetics 180: 977-993
Foll M, Fischer MC, Heckel G and L Excoffier (2010) Estimating population structure from AFLP amplification intensity. Molecular Ecology 19: 4638-4647
Fischer MC, Foll M, Excoffier L and G Heckel (2011) Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis). Molecular Ecology 20: 1450-1462