2011/12/21 by G. Guillot, Guillot, Gilles, Sabrina Renaud +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Environmental Science · #Animal Ecology and Behavior Studies #Applications (stat.AP) #Computation (stat.CO) #FOS: Biological sciences #FOS: Computer and information sciences #Genetic Mapping and Diversity in Plants and Animals #Genetic and phenotypic traits in livestock #Genetic diversity and population structure #Populations and Evolution (q-bio.PE) #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.1112.5006
openalex publication_date 2011/12/21 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Recognition of evolutionary units (species, populations) requires integrating\nseveral kinds of data such as genetic or phenotypic markers or spatial\ninformation, in order to get a comprehensive view concerning the\ndifferentiation of the units. We propose a statistical model with a double\noriginal advantage: (i) it incorporates information about the spatial\ndistribution of the samples, with the aim to increase inference power and to\nrelate more explicitly observed patterns to geography; and (ii) it allows one\nto analyze genetic and phenotypic data within a unified model and inference\nframework, thus opening the way to robust comparisons between markers and\npossibly combined analyzes. We show from simulated data as well are real data\nfrom the literature that our method estimates parameters accurately and\nimproves alternative approaches in many situations. The interest of this method\nis exemplified using an intricate case of inter- and intra-species\ndifferentiation based on an original data-set of georeferenced genetic and\nmorphometric markers obtained on em Myodes voles from Sweden. A computer\nprogram is made available as an extension of the R package Geneland.\n