© Matthieu Foll 2011

Detecting natural selection from population-based genetic data

BayeScan 2.1 is now officially released, allowing parallel computing on multicore machine, leading to much faster calculation. This version can also calculate q-value, a very useful measure of significance in the context of multiple testing.

BayeScan's original paper has now been cited more than 100 times!

BayeScan 2.0 is now officially released, implementing the new model for AFLP amplification intensity data developed at CMPG lab and supported by the Swiss National Science Foundation (grant No 3100A0-112072). Many other improvements are included, click "versions" section. The fist paper presenting and using it can be found here:
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

07.01.2011 BayeScan now has its own website, enjoy browsing!

27.09.2010 A new model for AFLP amplification intensity has been published by Matthieu Foll and colleagues, it will be incorporated in BayeScan soon...

BayeScan's original paper has been cited more than 50 times in the last year!

Andrés Pérez-Figueroa and his colleagues compared three different methods to detect selective loci using dominant markers (BayeScan, DFdist and DelSel). Details can be found in their publication but the main conclusion is summarized in this sentence taken from the abstract:
"Under a wide range of scenarios, we conclude that bayescan appears to be more efficient than the other methods, detecting a usually high percentage of true selective loci as well as less than 1% of outliers (false positives) under a fully neutral model. In addition, the percentage of outliers detected by this software is always correlated with the true percentage of selective loci in the genome."

BayeScan has been integrated in the BioHPC computer cluster application at Cornell University (CBSU). This means that you can simply use it from your favorite web browser at this page!

The paper presenting BayeScan is published.

The first version of BayeScan is officialy released.

Beginning of BayeScan development as part of Matthieu Foll's PhD, under the supervision of Oscar Gaggiotti.