<div dir="ltr">Hello, <div><br></div><div>changes are to be expected, as repeated genotypes form, by definition, clusters. So by adding/removing them you are effectively adding or removing clusters. Mathematically this is reflected by the variance components (total, between, within), which are all sums over individuals, and therefore change when adding / removing individuals.</div><div><br></div><div>In one case, your clustering solution will likely mostly reflect the presence of identical genotypes. In the second case, clusters will give an account of the diversity between unique genotypes. </div><div><br></div><div>Best</div><div>Thibaut</div></div><div class="gmail_extra"><br clear="all"><div><div class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><div><div><br>--<br>Dr Thibaut Jombart</div><div style="font-size:small">Lecturer, Department of Infectious Disease Epidemiology, Imperial College London</div></div><div><span style="font-size:12.8px">Head of RECON: </span><span style="font-size:12.8px"><a href="http://repidemicsconsortium.org" target="_blank">repidemicsconsortium.org</a></span><br></div></div><div><a href="http://sites.google.com/site/thibautjombart/" style="font-size:12.8px" target="_blank">sites.google.com/site/thibautjombart/</a><br></div><div><a href="http://github.com/thibautjombart" target="_blank">github.com/thibautjombart</a></div>Twitter: <a href="http://twitter.com/TeebzR" target="_blank">@TeebzR</a><br></div><div dir="ltr">+44(0)20 7594 3658</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
<br><div class="gmail_quote">On 24 April 2017 at 13:04, Adrien Rieux <span dir="ltr"><<a href="mailto:adrien.rieux@cirad.fr" target="_blank">adrien.rieux@cirad.fr</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div bgcolor="#FFFFFF" text="#000000">
<font face="Calibri">Hi there,<br>
<br>
</font>
<p class="MsoNormal"><font face="Calibri"><span lang="EN-GB">I’ve got a
question regarding the assessment of genetic structure from
microsatellite data
using the DAPC method. My dataset contains around 30% of
repeated genotypes. I
observe different and contrasted results (BIC as a function of
the number of
clusters) when I keep or exclude repeated genotypes
(find.clusters function).
Has someone ever experienced this situation and how would you
explain it ? I
would have predicted that finding the optimal number of
clusters should not be
influenced by repeated genotypes as the DAPC is only based on
the variation between
genotypes. Is there a general recommendation whether keeping
or excluding
repeated genotypes when performing DAPC ? <br>
</span></font></p>
<p class="MsoNormal"><font face="Calibri"><span lang="EN-GB"><br>
Cheers,<br>
</span></font></p>
<p class="MsoNormal"><font face="Calibri">Adrien</font><span class="HOEnZb"><font color="#888888"><br>
<span lang="EN-GB"><u></u><u></u></span></font></span></p><span class="HOEnZb"><font color="#888888">
<br>
<pre class="m_1273591718077142473moz-signature" cols="72">--
Adrien RIEUX
CIRAD - Dpt BIOS - UMR PVBMT
Tel: 0262499219
<a class="m_1273591718077142473moz-txt-link-freetext" href="https://adrienrieux.wordpress.com/home/" target="_blank">https://adrienrieux.wordpress.<wbr>com/home/</a></pre>
</font></span></div>
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