Perhaps you need two programs.

There is many programs to calculate Nei's genetic distance. Perhaps you coul use Popgene (https://www.ualberta.ca/~fyeh/popgene.html).

Then use R for clustering according to your distances matrix. You just need to download and call the cluster library with method="ward".

Hope this helps

Hi,

thank you for your reply, but clustering with R combined with pvclust (performing bootstrapping) needs to use the raw data (not the genetic distance matrix), and it is not possible -as far as I know- to calculate genetic distances (you can only calculate classical indices such as Euclidian distances). I can easily find softwares calculating genetic distances and perform after that a cluster analysis on the distance matrix with classical statistical softwares. But to include bootstrapping on the clustering everything must be perform together using the raw data. So I search for a software "all in one".

best regards

Fabienne

Hi Fabienne

So, what's the problem? Estimate the genetic distances with Popgene and cluster the samples, using raw data, with pvclust. 

Pablo

Hi,

I need to perform a cluster analysis based on unbiased Nei's genetic distances; the similarity indices available in pvclust are not appropriate. 

best regards

Fabienne

Have you tried PowerMarker?

Hello,

thank you very much for the suggestions of the softwares.

Unfortunately only uncorrected nei's genetic distances are calculated with these softwares, not the unbiased one (Nei 1978). The sample size varies a lot among the studied populations, so it is better to use the unbiased distance. But thanks! at least this gives some perspective!

best regards

fabienne

Hi,

Have you had a look at GenAlEx? As far as I am aware if calculates Nei's unbiased genetic distance matrix (see page 29 of the reference manual available here: http://biology-assets.anu.edu.au/GenAlEx/Download_files/GenAlEx%206.5b1%20Guide.pdf).

Hope this helps.

Thank you for your suggestion, but unfortunately the software does not perform cluster analyses.

best regards

fabienne