Distance‐based population classification software using mean‐field annealing
| Autor: | John R. Candy, Terry D. Beacham, Colin G. Wallace |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Genetics
Medical Population Single group Biology Software Salmon Statistics Genetics Animals Humans Computer Simulation education Cluster analysis Ecology Evolution Behavior and Systematics education.field_of_study business.industry Native american Ecology Genetics Population Microsatellite Mean field annealing business Algorithms Microsatellite Repeats Biotechnology Distance based |
| Zdroj: | Molecular Ecology Resources. 11:116-125 |
| ISSN: | 1755-0998 1755-098X |
| DOI: | 10.1111/j.1755-0998.2010.02902.x |
| Popis: | We describe a distance-based clustering method using a proximity matrix of genetic distances to partition populations into genetically similar groupings. The optimization heuristic mean-field annealing (MFA) was used to find locally optimal solutions where exhaustive search was not possible. To illustrate this method, we analysed both simulated and real data sets. Simulated data indicated that MFA successfully differentiated population groups, even with small F(ST) values, as long as there was separation of within and between group distances. Reanalysis of microsatellite data from various human populations using mean-fields found similar ethnic groups corresponding to major geographic regions reported by Rosenberg et al. (2002) who used the model-based computer program Structure. However, with MFA, the Kalash population was found to group with other Central/South Asian populations instead of being the only member of its own genetic cluster. Europe/Middle East populations formed a separate group from Central/South Asian populations instead of being a single group in the Structure analysis. The MFA analysis determined the greatest genetic distances (largest mean intracluster distance) occurred in native American populations, identifying three groups instead of only one found with Structure. For conservation purposes, it is not only important to identify genetically similar groupings but also to determine the relative level of genetic differentiation captured within these groups. To illustrate this, we compare two separate MFA analyses of Chinook salmon (Oncorhynchus tshawytscha) populations from British Columbia, Canada. The software called PORGS-MFA used in this article can be downloaded from http://www.pac.dfo-mpo.gc.ca/science/facilities-installations/pbs-sbp/mgl-lgm/apps/porgs/index-eng.htm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text