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Is a Multivariate Consensus Representation of Genetic Relationships Among Populations Always Meaningful?
Author(s) -
Katayoun Moazami-Goudarzi,
Dénis Laloë
Publication year - 2002
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1093/genetics/162.1.473
Subject(s) - multivariate statistics , biology , multivariate analysis , principal component analysis , typology , phylogenetic tree , reliability (semiconductor) , population , genetics , microsatellite , representation (politics) , evolutionary biology , computational biology , statistics , mathematics , allele , geography , demography , power (physics) , physics , archaeology , quantum mechanics , sociology , politics , political science , law , gene
To determine the relationships among closely related populations or species, two methods are commonly used in the literature: phylogenetic reconstruction or multivariate analysis. The aim of this article is to assess the reliability of multivariate analysis. We describe a method that is based on principal component analysis and Mantel correlations, using a two-step process: The first step consists of a single-marker analysis and the second step tests if each marker reveals the same typology concerning population differentiation. We conclude that if single markers are not congruent, the compromise structure is not meaningful. Our model is not based on any particular mutation process and it can be applied to most of the commonly used genetic markers. This method is also useful to determine the contribution of each marker to the typology of populations. We test whether our method is efficient with two real data sets based on microsatellite markers. Our analysis suggests that for closely related populations, it is not always possible to accept the hypothesis that an increase in the number of markers will increase the reliability of the typology analysis.

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