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  • 标题:On the Informativeness of Dominant and Co-Dominant Genetic Markers for Bayesian Supervised Clustering
  • 本地全文:下载
  • 作者:Gilles Guillot ; Alexandra Carpentier-Skandalis
  • 期刊名称:Open Statistics & Probability Journal
  • 电子版ISSN:1876-5270
  • 出版年度:2011
  • 卷号:3
  • 期号:1
  • 页码:7-12
  • DOI:10.2174/1876527001103010007
  • 出版社:Bentham open
  • 摘要:

    We study the accuracy of a Bayesian supervised method used to cluster individuals into genetically homogeneous groups on the basis of dominant or codominant molecular markers. We provide a formula relating an error criterion to the number of loci used and the number of clusters. This formula is exact and holds for arbitrary number of clusters and markers. Our work suggests that dominant markers studies can achieve an accuracy similar to that of codominant markers studies if the number of markers used in the former is about 1.7 times larger than in the latter.

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