[adegenet-forum] dapc

[Zhian Kamvar]

Hi,

DAPC is very sensitive to the number of PC you choose. I suspect what may
be happening here is that you have picked exactly the same number of PC in
your DAPC as you chose to pick your clusters. This results in a bit of
circular logic where you are asking the discriminant function to
discriminate your groups based on the exact principal components you used
to define your groups. Because of that, the between-group separation is so
vast that your within group differences is negligible.

Instead, what you should do is use the xvalDapc function to perform a
cross-validation to avoid over-fitting.

Best,
Zhian

On Sun, Oct 28, 2018 at 11:00 AM <
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>    1. dapc (amir naji)
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> Message: 1
> Date: Fri, 27 Oct 2017 19:44:03 +0330
> From: amir naji <amnaji1970 at yahoo.com>
> To: "adegenet-forum at lists.r-forge.r-project.org"
>         <adegenet-forum at lists.r-forge.r-project.org>
> Subject: [adegenet-forum] dapc
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> Hi
> I read my dart date set using dart R  package (62 genotype and 12500 snp
> loci).
> I built a DAPC scatter plot   without using a priori grouping information
> using this command line: dapc <- dapc(data, grp$grp).grp was created by
> using find.clusters command. But in scatter plot (I used scatter(dapc)
> command) only three points representing each group were seen and
> individuals were not shown in scatter plot.  I couldn?t find the reason and
> I hope to got help on that.
> Thanks for your help
> Amir
>
>
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