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A new FST method to uncover local adaptation using environmental variables
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dc.contributor.author | de Villemereuil, Pierre | |
dc.contributor.author | Gaggiotti, Oscar Eduardo | |
dc.date.accessioned | 2016-07-18T23:30:57Z | |
dc.date.available | 2016-07-18T23:30:57Z | |
dc.date.issued | 2015-11-09 | |
dc.identifier.citation | de Villemereuil , P & Gaggiotti , O E 2015 , ' A new F ST method to uncover local adaptation using environmental variables ' , Methods in Ecology and Evolution , vol. 6 , no. 11 , pp. 1248-1258 . https://doi.org/10.1111/2041-210X.12418 | en |
dc.identifier.issn | 2041-210X | |
dc.identifier.other | PURE: 192095619 | |
dc.identifier.other | PURE UUID: f6c1c632-882e-4ebd-9485-51d903ea6ef7 | |
dc.identifier.other | Scopus: 84955175412 | |
dc.identifier.other | WOS: 000367743700002 | |
dc.identifier.other | ORCID: /0000-0003-1827-1493/work/61370100 | |
dc.identifier.uri | https://hdl.handle.net/10023/9159 | |
dc.description | PdV was supported by a doctoral studentship from the French Ministère de la Recherche et de l'Enseignement Supérieur. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS). | en |
dc.description.abstract | 1. Genome-scan methods are used for screening genome-wide patterns of DNA polymorphism to detect signatures of positive selection. There are two main types of methods: (i) "outlier'' detection methods based on FST that detect loci with high differentiation compared to the rest of the genome, and (ii) environmental association methods that test the association between allele frequencies and environmental variables. 2. We present a new FST-based genome-scan method, BayeScEnv, which incorporates environmental information in the form of "environmental differentiation''. It is based on the F-model, but, as opposed to existing approaches, it considers two locus-specific effects; one due to divergent selection, and another due to various other processes different from local adaptation (e.g. range expansions, differences in mutation rates across loci or background selection). The method was developped in C++ and is avaible at http://github.com/devillemereuil/bayescenv. 3. A simulation study shows that our method has a much lower false positive rate than an existing FST-based method, BayeScan, under a wide range of demographic scenarios. Although it has lower power, it leads to a better compromise between power and false positive rate. 4. We apply our method to a human dataset and show that it can be used successfully to study local adaptation. We discuss its scope and compare it to other existing methods. | |
dc.format.extent | 11 | |
dc.language.iso | eng | |
dc.relation.ispartof | Methods in Ecology and Evolution | en |
dc.rights | © 2015 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1111/2041-210X.12418 | en |
dc.subject | Local adaptation | en |
dc.subject | Environment | en |
dc.subject | Bayesian methods | en |
dc.subject | F model | en |
dc.subject | False discovery rate | en |
dc.subject | Genome scan | en |
dc.subject | QH301 Biology | en |
dc.subject | BDC | en |
dc.subject | R2C | en |
dc.subject.lcc | QH301 | en |
dc.title | A new FST method to uncover local adaptation using environmental variables | en |
dc.type | Journal article | en |
dc.description.version | Postprint | en |
dc.contributor.institution | University of St Andrews. School of Biology | en |
dc.contributor.institution | University of St Andrews. Marine Alliance for Science & Technology Scotland | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.identifier.doi | https://doi.org/10.1111/2041-210X.12418 | |
dc.description.status | Peer reviewed | en |
dc.date.embargoedUntil | 2016-07-19 |
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