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<div style="direction: ltr;font-family: Tahoma;color: #000000;font-size: 10pt;">Hi Robert,
<br>
<br>
this has been discussed before on the forum. I would recommend using xvalDapc over optim.a.score. The procedure is documented in the vignette, and explained in more details in the last instance of the DAPC practical I use for workshop (adegenet website > documents,
bottom of the page):<br>
<br>
<a href="http://adegenet.r-forge.r-project.org/files/Barcelona2015/practical-MVAgroups.1.0.pdf" target="_blank">http://adegenet.r-forge.r-project.org/files/Barcelona2015/practical-MVAgroups.1.0.pdf</a><br>
<br>
Cheers<br>
Thibaut<br>
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<div class="PlainText"> <br>
==============================<br>
Dr Thibaut Jombart<br>
MRC Centre for Outbreak Analysis and Modelling<br>
Department of Infectious Disease Epidemiology<br>
Imperial College - School of Public Health<br>
Norfolk Place, London W2 1PG, UK<br>
Tel. : 0044 (0)20 7594 3658<br>
http://sites.google.com/site/thibautjombart/<br>
http://sites.google.com/site/therepiproject/<br>
http://adegenet.r-forge.r-project.org/<br>
Twitter: @thibautjombart<br>
<br>
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<div style="direction: ltr;" id="divRpF317277"><font color="#000000" face="Tahoma" size="2"><b>From:</b> adegenet-forum-bounces@lists.r-forge.r-project.org [adegenet-forum-bounces@lists.r-forge.r-project.org] on behalf of Robert Fairweather [osue37@bangor.ac.uk]<br>
<b>Sent:</b> 13 November 2015 17:53<br>
<b>To:</b> adegenet-forum@lists.r-forge.r-project.org<br>
<b>Subject:</b> [adegenet-forum] optimum number of PCs for optim.a.score()<br>
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<p class="MsoNormal">Hello,</p>
<p class="MsoNormal">I am using the optim.a.score() function to investigate the optimum number of PCs to retain in my analysis, a function that operates on a DAPC object. To produce a DAPC object I first have to carry out a DAPC procedure on my data, which
means defining the number of PCs to retain in advance. I have noticed that the number of PCs retained in the DAPC object changes the outcome of the optim.a.score function, suggesting that some optimum should be known before using the function.
</p>
<p class="MsoNormal">For example, with the microbov data, <b><span style="font-family:"Courier New"">optim.a.score(dapc(microbov, n.da=100, n.pca=50))</span></b> , as suggested in the vignette, returns an optimum number of ~22 PCs, however, increasing this
to 100, 200 and 300 PCs, all explaining <100% cumulative variance, return values of 15, 27 and 59 respectively. 300 returns a series of instability warnings.
</p>
<p class="MsoNormal">With this in mind, what is the best way to choose the number of PCs in the dapc object used in optim.a.score()? The number used in the microbov example in the vignette (50) is that explaining ~90% cumulative variance, and thus far I have
been using that threshold as a guide with my own data. </p>
<p class="MsoNormal">Am I perhaps misunderstanding the use of the function?</p>
<p class="MsoNormal">Many thanks,</p>
<p class="MsoNormal">Robert</p>
<p class="MsoNormal"> </p>
<p class="MsoNormal"><span style="color:#2E74B5">Robert Fairweather</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Research Student</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Molecular Ecology and Fisheries Genetics Laboratory</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Environment Centre Wales</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Bangor Unversity</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">LL57 2UW</span></p>
<p class="MsoNormal"><span style="color:#2E74B5"> </span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Email: <a href="mailto:osue37@bangor.ac.uk" target="_blank">
osue37@bangor.ac.uk</a></span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Skype: fairweathr</span></p>
<p class="MsoNormal"><span style="color:#2E74B5">Twitter: @FairweathR</span></p>
<p class="MsoNormal"> </p>
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