BayeScan 2.1 – Detect Natural Selection from Population-base Genetic Data

BayeScan 2.1


BayeScan ( (BAYEsian genome SCAN for outliers) ) 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 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



Computational and Molecular Population Genetics Lab, University of Bern







Mol Ecol. 2011 Apr;20(7):1450-62. doi: 10.1111/j.1365-294X.2011.05015.x.
Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis).
Fischer MC, Foll M, Excoffier L, Heckel G.

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