[R-sig-phylo] Nucleotide diversity - different definitions and algorithms: pegas vs Arlequin
Good day all, The estimate of nucleotide diversity vary hugely between pegas and Arlequin, yet they both cite Nei (1987). For example, Arlequin = 0.7158 pegas = 0.003926426 With the same dataset. Their definitions of nucleotide diversity are also very different: Arlequin: It is computed here as the probability that two randomly chosen homologous (nucleotide or RFLP) sites are different. pegas: The nucleotide diversity is the sum of the number of differences between pairs of sequences divided by the number of comparisons (i.e. /n(n - 1)/2/, where /n/ is the number of sequences). Now, which is correct? Or more correct? How are they linked? Which should I use in a paper? Thanks very much for any help, Confused Al ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Re: [R-sig-phylo] Nucleotide diversity - different definitions and algorithms: pegas vs Arlequin
Hi Alastair,
Alastair Potts wrote on 01/08/2011 14:19:
Good day all,
The estimate of nucleotide diversity vary hugely between pegas and
Arlequin, yet they both cite Nei (1987).
For example,
Arlequin = 0.7158
pegas = 0.003926426
With the same dataset.
Their definitions of nucleotide diversity are also very different:
Arlequin: It is computed here as the probability that two randomly
chosen homologous (nucleotide or RFLP) sites are different.
pegas: The nucleotide diversity is the sum of the number of differences
between pairs of sequences divided by the number of comparisons (i.e.
/n(n - 1)/2/, where /n/ is the number of sequences).
This is a way to calculate the above. Here's a function that samples
randomly one site and two rows of a set of DNA sequences a large number
of times and returns the proportion of cases where the two nucleotides
were different:
f - function(x, nrep = 1e4)
{
n - nrow(x)
s - ncol(x)
count - 0
for (i in 1:nrep) {
y - x[sample(n, 2), sample(s, 1), drop = TRUE]
if (y[1] != y[2]) count - count + 1
}
count / nrep
}
It requires to have no ambiguous data, eg:
library(phangorn)
data(Laurasiatherian)
X - as.DNAbin(Laurasiatherian)
f(X)
[1] 0.1458
nuc.div(X)
[1] 0.1448687
Can you try this on your data?
Cheers,
Emmanuel
Now, which is correct? Or more correct? How are they linked? Which
should I use in a paper?
Thanks very much for any help,
Confused Al
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--
Emmanuel Paradis
IRD, Jakarta, Indonesia
http://ape.mpl.ird.fr/
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Re: [R-sig-phylo] Nucleotide diversity - different definitions and algorithms: pegas vs Arlequin
Hi Emmanuel,
Thanks for function. However, the problem actually lies with my
misunderstanding of the the Arlequin output - I was mistaking the gene
diversity result with nucleotide diversity (nucleotide diversity is the
gene diversity divided by L loci). Both of your functions produce very
similar results as to what is produced by Arlequin when I look up the
correct nucleotide diversity.
My humblest apologies for wasting your time,
Cheers,
Incompetent Al
On 2011/08/01 02:59 PM, Emmanuel Paradis wrote:
Hi Alastair,
Alastair Potts wrote on 01/08/2011 14:19:
Good day all,
The estimate of nucleotide diversity vary hugely between pegas and
Arlequin, yet they both cite Nei (1987).
For example,
Arlequin = 0.7158
pegas = 0.003926426
With the same dataset.
Their definitions of nucleotide diversity are also very different:
Arlequin: It is computed here as the probability that two randomly
chosen homologous (nucleotide or RFLP) sites are different.
pegas: The nucleotide diversity is the sum of the number of
differences between pairs of sequences divided by the number of
comparisons (i.e. /n(n - 1)/2/, where /n/ is the number of sequences).
This is a way to calculate the above. Here's a function that samples
randomly one site and two rows of a set of DNA sequences a large
number of times and returns the proportion of cases where the two
nucleotides were different:
f - function(x, nrep = 1e4)
{
n - nrow(x)
s - ncol(x)
count - 0
for (i in 1:nrep) {
y - x[sample(n, 2), sample(s, 1), drop = TRUE]
if (y[1] != y[2]) count - count + 1
}
count / nrep
}
It requires to have no ambiguous data, eg:
library(phangorn)
data(Laurasiatherian)
X - as.DNAbin(Laurasiatherian)
f(X)
[1] 0.1458
nuc.div(X)
[1] 0.1448687
Can you try this on your data?
Cheers,
Emmanuel
Now, which is correct? Or more correct? How are they linked? Which
should I use in a paper?
Thanks very much for any help,
Confused Al
___
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R-sig-phylo@r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
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