BayeScan¶
Description¶
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.
Environment Modules¶
Run module spider bayescan to find out what environment modules are available for this application.
Environment Variables¶
- HPC_BAYESCAN_DIR - installation directory
- HPC_BAYESCAN_BIN - executable directory
- HPC_BAYESCAN_DOC - documentation directory
- HPC_BAYESCAN_EXE - examples directory
- HPC_BAYESCAN_R - R functions directory
Citation¶
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
Categories¶
biology, variant_calling