dist.genet(genet, method = 1, diag = FALSE, upper = FALSE)
genet
print.dist
print.dist
dist
between the rows of the data framemethod
computes the distance matrices between populations using the frequencies $p_{ij}^k$.
1. Nei's distance:
$D_1(a,b)=- \ln(\frac{\sum_{k=1}^{\nu} \sum_{j=1}^{m(k)}
p_{aj}^k p_{bj}^k}{\sqrt{\sum_{k=1}^{\nu} \sum_{j=1}^{m(k)}
{(p_{aj}^k) }^2}\sqrt{\sum_{k=1}^{\nu} \sum_{j=1}^{m(k)}
{(p_{bj}^k)}^2}})$
2. Angular distance or Edwards' distance:
$D_2(a,b)=\sqrt{1-\frac{1}{\nu} \sum_{k=1}^{\nu}
\sum_{j=1}^{m(k)} \sqrt{p_{aj}^k p_{bj}^k}}$
3. Coancestrality coefficient or Reynolds' distance:
$D_3(a,b)=\sqrt{\frac{\sum_{k=1}^{\nu}
\sum_{j=1}^{m(k)}{(p_{aj}^k - p_{bj}^k)}^2}{2 \sum_{k=1}^{\nu} (1-
\sum_{j=1}^{m(k)}p_{aj}^k p_{bj}^k)}}$
4. Classical Euclidean distance or Rogers' distance:
$D_4(a,b)=\frac{1}{\nu} \sum_{k=1}^{\nu} \sqrt{\frac{1}{2}
\sum_{j=1}^{m(k)}{(p_{aj}^k - p_{bj}^k)}^2}$
5. Absolute genetics distance or Provesti 's distance:
$D_5(a,b)=\frac{1}{2{\nu}} \sum_{k=1}^{\nu} \sum_{j=1}^{m(k)}
|p_{aj}^k - p_{bj}^k|$Distance 2: Edwards, A.W.F. (1971) Distance between populations on the basis of gene frequencies. Biometrics, 27, 873--881. Cavalli-Sforza L.L. and Edwards A.W.F. (1967) Phylogenetic analysis: models and estimation procedures. Evolution, 32, 550--570. Hartl, D.L. and Clark, A.G. (1989) Principles of population genetics. Sinauer Associates, Sunderland, Massachussetts (p. 303).
Distance 3: Reynolds, J. B., B. S. Weir, and C. C. Cockerham. (1983) Estimation of the coancestry coefficient: basis for a short-term genetic distance. Genetics, 105, 767--779.
Distance 4: Rogers, J.S. (1972) Measures of genetic similarity and genetic distances. Studies in Genetics, Univ. Texas Publ., 7213, 145--153. Avise, J. C. (1994) Molecular markers, natural history and evolution. Chapman & Hall, London.
Distance 5:
Prevosti A. (1974) La distancia gen�tica entre poblaciones. Miscellanea Alcob�, 68, 109--118.
Prevosti A., Oca�a J. and Alonso G. (1975) Distances between populations of Drosophila subobscura, based on chromosome arrangements frequencies. Theoretical and Applied Genetics, 45, 231--241.
To find some useful explanations:
Sanchez-Mazas A. (2003) Cours de G�n�tique Mol�culaire des Populations. Cours VIII Distances g�n�tiques - Repr�sentation des populations.
data(casitas)
casi.genet <- char2genet(casitas,
as.factor(rep(c("dome", "cast", "musc", "casi"), c(24,11,9,30))))
ldist <- lapply(1:5, function(method) dist.genet(casi.genet,method))
ldist
unlist(lapply(ldist, is.euclid))
kdist(ldist)
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