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J. Relethford (1996)
Genetic drift can obscure population history: problem and solution.Human biology, 68 1
T. Weaver (2016)
Estimators for QST and coalescence timesEcology and Evolution, 6
J. Relethford, M. Crawford (2013)
Genetic drift and the population history of the Irish travellers.American journal of physical anthropology, 150 2
J. H. Relethford (2007)
Anthropological genetics: Theory, methods and applications
J. Long, R. Kittles (2003)
Human Genetic Diversity and the Nonexistence of Biological RacesHuman Biology, 75
J. Relethford (1988)
Estimation of kinship and genetic distance from surnames.Human biology, 60 3
R. Lewontin (1972)
The Apportionment of Human Diversity
C. Roseman, T. Weaver (2004)
Multivariate apportionment of global human craniometric diversity.American journal of physical anthropology, 125 3
W. W. Howells (1989)
Skull shapes and the map: Craniometric analyses in the dispersion of modern homo. Papers of the Peabody Museum of Archaeology and Ethnology No. 79
J. Relethford (2001)
Global Analysis of Regional Differences in Craniometric Diversity and Population SubstructureHuman Biology, 73
E. M. Cramer, W. A. Nicewander (1979)
Some symmetric, invariant measures of multivariate association, 44
J. Relethford (1994)
Craniometric variation among modern human populations.American journal of physical anthropology, 95 1
L. W. Konigsberg (2006)
Bioarchaeology: The contextual analysis of human remains
J. Relethford, F. Lees (1982)
The use of quantitative traits in the study of human population structureAmerican Journal of Physical Anthropology, 25
J. Relethford, Michael Crawford, J. Blangero (1997)
Genetic drift and gene flow in post-famine Ireland.Human biology, 69 4
W. W. Howells (1973)
Methods and theories of anthropological genetics
J. Relethford, J. Blangero (1990)
Detection of differential gene flow from patterns of quantitative variation.Human biology, 62 1
P. Key, R. Jantz (1981)
A multivariate analysis of temporal change in Arikara craniometrics: a methodological approach.American journal of physical anthropology, 55 2
J. H. Relethford (2016)
Biological distance analysis: Forensic and bioarchaeological perspectives
P. Key, R. L. Jantz (1981)
A multivariate analysis of temporal change in Arikara craniometrics, 55
J. Blangero (1990)
Population structure analysis using polygenic traits: estimation of migration matrices.Human biology, 62 1
S. Wright (1950)
Genetical structure of populations.Nature, 166 4215
S. Williams-Blangero, J. Blangero (1989)
Anthropometric variation and the genetic structure of the Jirels of Nepal.Human biology, 61 1
J. C. Long, R. A. Kittles (2003)
Human genetic diversity and the nonexistence of human races, 75
J. Stevens (1996)
Applied multivariate statistics for the social sciences
C. C. Roseman, T. D. Weaver (2004)
Multivariate apportionment of human global craniometric diversity, 125
N. Saino, A. Bolzern, A. Møller (1997)
Immunocompetence, ornamentation, and viability of male barn swallows (Hirundo rustica).Proceedings of the National Academy of Sciences of the United States of America, 94 2
R. R. Sokal, F. J. Rohlf (1995)
Biometry: The principles and practice of statistics in biological research
Blangero J. (1990)
27Human Biology, 62
J. Relethford (2002)
Apportionment of global human genetic diversity based on craniometrics and skin color.American journal of physical anthropology, 118 4
A. Rogers, H. Harpending (1986)
MIGRATION AND GENETIC DRIFT IN HUMAN POPULATIONSEvolution, 40
Studies of anthropological genetics and bioarcheology often examine the degree of among‐group variation in quantitative traits such as craniometrics and anthropometrics. One comparative index of among‐group differentiation is the minimum value of Wright's FST as estimated from quantitative traits. This measure has been used in certain population‐genetic applications such as comparison with FST estimated from genetic data, although some inferences are limited by how well the data and study design fit the underlying population‐genetic model. In many cases, all that is needed is a simple measure of among‐group variation. One such measure is R2, the proportion of total phenotypic variation accounted for by among‐group phenotypic variation, a measure easily obtained from analysis of variance and regression methods. This paper shows that R2 and minimum FST are closely related as MinFST≈R2/2−R2. R2 is computationally easy and may be useful in cases where all we need is a simple measure of relative among‐group differentiation.
American Journal of Physical Anthropology – Wiley
Published: Jul 1, 2023
Keywords: analysis of variance; F ST; R 2; quantitative traits
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