[adegenet-forum] Understanding DAPC scatter plot

[Zhian Kamvar]

The colours are of the a-priori groups because the information about the
posterior assignments are spatially contained on the axes themselves.

The colours help you understand how well the data matches these a-priori
groups, as kind of a visual representation of AMOVA.

I hope that helps,
Zhian

On Fri, May 13, 2022 at 3:08 AM <
adegenet-forum-request at lists.r-forge.r-project.org> wrote:

> Date: Thu, 12 May 2022 19:44:32 +0000
> From: Nikki Vollmer <nlv209 at hotmail.com>
> To: "adegenet-forum at lists.r-forge.r-project.org"
>         <adegenet-forum at lists.r-forge.r-project.org>
> Subject: [adegenet-forum] Understanding DAPC scatter plot
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> Hi!
> I am looking for a better understanding of the DAPC scatter plot. Is it
> correct that with the code below, after running the DAPC, the scatter plot
> is plotting/color-coding based on the prior groups? If so, why not the
> posterior groups? I thought that the result of running a DAPC is the
> posterior group information and I just figured that is what the scatter
> plot would be showing me, but perhaps I am not understanding something
> correctly?  I know that you can look at the posterior information with
> compoplot, I am now just wanting to know how to correctly interpret scatter
> plots when I see them.
>
> the basic code I am referring to is:
> data_scaled <- tab(data,NA.method="mean")
> grp<-find.clusters(data_scaled, max.n.clust=40)
> dapc1<-dapc(data_scaled, grp$grp)
> scatter(dapc1)
>
> I appreciate any help with clarifying this!
> Nikki
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