Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study

Wiley - Tập 7 Số 5 - Trang 747-756 - 2007
Chibiao Chen1,2, Éric Durand3, Florence Forbes1, Olivier François3
1MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems (Inria Grenoble - Rhône-Alpes 655 avenue de l'Europe - Montbonnot 38334 Saint Ismier Cedex - France)
2TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (Domaine de la Merci, 38706 La Tronche, France - France)
3TIMB (France)

Tóm tắt

AbstractOn the basis of simulated data, this study compares the relative performances of the Bayesian clustering computer programs structure, geneland, geneclust and a new program named tess. While these four programs can detect population genetic structure from multilocus genotypes, only the last three ones include simultaneous analysis from geographical data. The programs are compared with respect to their abilities to infer the number of populations, to estimate membership probabilities, and to detect genetic discontinuities and clinal variation. The results suggest that combining analyses using tess and structure offers a convenient way to address inference of spatial population structure.

Từ khóa


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Thông tin
Thông tin xuất bản

Wiley

Tập 7 Số 5

747-756

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