I would like to ask you for your sugestions for selecting a test to detect signatures of selection in the following mouse model:
We have three groups: animals exhibiting trait A, trait B and controls. These animals were selected over the last 4 decades (controls were mated randomly and do not show any of the traits). That is total 170 generations (~4 generations per year).
We want to detect the genomic signatures of selection for trait A and B.
I am new in population genomics, but according to this paper (http://www.ncbi.nlm.nih.gov/pubmed/21218185), showing a desition tree (fig 1). I should apply a the Fst and a Linckage 'Desequilibrium test, given that the time scale would be short (40 years, 170 generations) and there are multiple populations.
Could you corroborate if this is the correct approach?
Thanks
Answer
I am assuming in this answer that you do not have any information about what environment is affecting the selection pressure so that methods like Bayenv2 can't be used.
The standard algorithms are:
- Lewontin-Krakauer test
- fdist
- BayeScan
- FLK
- PCAdapt
Whitlock and Lotterhos 2014 showed that most often FLK and Bayenv2 perform better than the the three others. A number of articles (Meirmans 2012, Bierne et al 2013, De Mita et al 2013 and Fourcade et al 2013) have also shown that fdist and BayeScan suffer from high false positive rate. I would therefore recommend to go with FLK but I am probably not good enough to give very good advice.
Note that you should learn a bit about how these algorithms work and not using them blindly.
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