title: The apportionment of total genetic variation by categorical analysis of variance.
abstract: We wish to suggest the categorical analysis of variance as a means of quantifying the proportion of total genetic variation attributed to different sources of variation. This method potentially challenges researchers to rethink conclusions derived from a well-known method known as the analysis of molecular variance (AMOVA). The CATANOVA framework allows explicit definition, and estimation, of two measures of genetic differentiation. These parameters form the subject of interest in many research programmes, but are often confused with the correlation measures defined in AMOVA, which cannot be interpreted as relative contributions of particular sources of variation. Through a simulation approach, we show that under certain conditions, researchers who use AMOVA to estimate these measures of genetic differentiation may attribute more than justified amounts of total variation to population labels. Moreover, the two measures can also lead to incongruent conclusions regarding the genetic structure of the populations of interest. Fortunately, one of the two measures seems robust to variations in relative sample sizes used. Its merits are illustrated in this paper using mitochondrial haplotype and amplified fragment length polymorphism (AFLP) data.
authors.affiliation: National University of Singapore. mrtfkhang@yahoo.com
authors.forename: Tsung Fei
authors.initials: TF
authors.lastname: Khang
authors.forename: Von Bing
authors.initials: VB
authors.lastname: Yap
mesh_terms: D000465:Algorithms; D054458:Amplified Fragment Length Polymorphism Analysis / Q000706:statistics & numerical data; D000704:Analysis of Variance; D000818:Animals; D019659:Asteraceae / Q000235:genetics; D056808:Biostatistics; D029759:Calophyllum / Q000235:genetics; D004272:DNA, Mitochondrial / Q000235:genetics; D014644:Genetic Variation; D005828:Genetics, Population / Q000706:statistics & numerical data*; D023281:Genomics / Q000706:statistics & numerical data; D006239:Haplotypes; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D049911:Pinctada / Q000235:genetics; D044469:Racial Groups / Q000235:genetics
chemical_list: D004272:DNA, Mitochondrial