Pregled bibliografske jedinice broj: 328481
Overview of Genetic Boundary Detection Methods and their Aplication in Population Genetics
Overview of Genetic Boundary Detection Methods and their Aplication in Population Genetics // 43rd Croatian & 3rd International Symposium on Agriculture Book of Abstracts / Milan Pospišil (ur.).
Zagreb: Agronomski fakultet Sveučilišta u Zagrebu, 2008. (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 328481 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Overview of Genetic Boundary Detection Methods and their Aplication in Population Genetics
Autori
Safner, Toni ; Gunjača, Jerko ; Manel, Stéphanie
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
43rd Croatian & 3rd International Symposium on Agriculture Book of Abstracts
/ Milan Pospišil - Zagreb : Agronomski fakultet Sveučilišta u Zagrebu, 2008
ISBN
978-953-6135-68-4
Skup
43rd Croatian & 3rd International Symposium on Agriculture
Mjesto i datum
Opatija, Hrvatska, 18.02.2008. - 21.02.2008
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Population genetics; Genetic boundaries; Spatial clustering
Sažetak
Identification of the spatial pattern of biodiversity is important for understanding underlying biological, physiological or demographical processes. Delineation of genetic boundaries (i.e. detection of areas of sharp change in allele frequencies) is potential approach to describe such patterns. In the recent time, there is a growing interest in applications of spatial analyses to identify genetic discontinuities and an increasing number of statistical methods implemented in freely available software. In this project, we evaluate some of the existing methods by its performances for both empirical and simulated datasets. We included some of the Bayesian spatial clustering methods (TESS, BAPS and Geneland) and two other methods (Wombling and Monmonier’ s algorithm). Preliminary results show that Bayesian clustering methods perform better than two other methods, both on simulated and different types of empirical data.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Poljoprivreda (agronomija)
POVEZANOST RADA
Projekti:
178-1780691-0688 - Povećanje učinkovitosti istraživanja primjenom naprednih biometrijskih modela (Gunjača, Jerko, MZOS ) ( CroRIS)
Ustanove:
Agronomski fakultet, Zagreb