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<p>Dear Adegenet users,</p>
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<p>I am trying to perform a PCA on whole genome SNP data, and the results I have so far seem to make sense. I do have a few doubts though, and I may need some help to solve them.</p>
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<p>Following variant calling, I converted my data to a dataframe, e.g:</p>
<p>mysnps<- data.frame('ind_names'= c('s1', 's2', 's3'), 'locus1'=c('A/A', 'N', 'A/G'), 'locus2'=c('G/G', 'A/G', A/A'))<br>
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<p>Then I used df2genind on the dataframe, and performed the principal component analysis. </p>
<p>Was that right? I am still not sure if I should have rather used a genlight object. Should I change it if I decide to do DAPC or PCoA?<br>
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<p>Thanks for your kind help,</p>
<p>Max<br>
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<div style="font-family:Tahoma; font-size:13px">Massimiliano S. Tagliamonte</div>
<div style="font-family:Tahoma; font-size:13px">Graduate Student</div>
<div style="font-family:Tahoma; font-size:13px">University of Florida<br>
College of Veterinary Medicine</div>
<div style="font-family:Tahoma; font-size:13px">Department of Infectious Diseases and Pathology<br>
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