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Hi Thibaut
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<div class="">I’ve got a question about how to best<span class=""><b class=""> </b>scale genetic and morphometric data for a combined Principal Component Analysis</span> of both datasets using <font face="Courier New" class="">R/adegenet</font>. Scaling of
genetic data has already been a topic on the adegenet forum, but I think not in combination with morphological data.</div>
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<div class="">Here is where I am unsure: I'm using <font face="Courier New" class="">dfssr <- adegenet::df2genind(datassr)</font> to create an allele table of microsatellite data, then I use <font face="Courier New" class="">dfcombi <- cbind(dfssr@tab, dfmorpho)</font> to
combine the genetic data with morphometric data of the same diploid samples. Now I want to use <font face="Courier New" class="">PCA(dfcombi) </font>to analyze the combined genetic and morphometric data in an integrative way. Scaling of the morphometric variables
is important since the morphometric dataset contains variables measured on very different units, and variables with large variances would load the principal components too heavily compared to other, perhaps important variables with lower absolute variance.
By contrast, scaling of the allele table (coded as 0, 1, 2 as in the <font face="Courier New" class="">
@tab</font> slot of <font face="Courier New" class="">genind</font> objects) will (at least I think) lead to the principal components being more loaded by very rare alleles and very common alleles (i.e. those variables with low variance).</div>
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<div class="">Since you have a lot of experience with multivariate genetic data, what would you suggest? </div>
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<div class="">1) Scaling of the morphometric data only and cbind it with the unscaled allele table to perform
<font face="Courier New" class="">PCA(dfcombi.dfmorpho.already.scaled, scale.unit = F)</font>?</div>
<div class="">2) Scaling of the morphometric data and the allele table, i.e. <span style="font-family: 'Courier New';" class="">PCA(dfcombi, scale.unit = T)</span>? </div>
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<div class="">The goal of the integrated PC analysis is to find entities that represent single species in a multispecies dataset. </div>
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<div class="">Thank you in advance</div>
<div class="">Simon</div>
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<div class="">**********************************************</div>
Simon Crameri</div>
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ETH Zurich</div>
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Ph.D. candidate<br class="">
Plant Ecological Genetics<br class="">
Institute of Integrative Biology (IBZ)<br class="">
Department of Environmental Systems Science</div>
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Universitätstrasse 16, CHN G27<br class="">
8092 Zurich, Switzerland<br class="">
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E-mail: <a href="mailto:simon.crameri@env.ethz.ch" class="">simon.crameri@env.ethz.ch</a></div>
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<a href="mailto:niklaus.zemp@env.ethz.ch" class=""></a>Web: <a href="http://www.peg.ethz.ch/" class="">www.peg.ethz.ch</a></div>
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