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        HELENA IBANEZ MARTINEZ <<a href="mailto:him21024@um.es">him21024@um.es</a>> escribió:</p>
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                HELENA IBANEZ MARTINEZ <<a href="mailto:him21024@um.es">him21024@um.es</a>> escribió:</p>
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                <span class="tlid-translation translation"><span title=""><strong><span class="tlid-translation translation"><span title="">Hello, my name is Helena,<br><br><span class="tlid-translation translation"><span title="">I have a question about my DAPC analayses.<br><br><span class="tlid-translation translation"><span title="">I'm following the tutorial step by step and I get the DAPC graph of my data very well, but my problem is when I repeat the process my graphic results come out completely different every time...</span><br><br><span title="">My question is, why do such different results come out if I'm repeating exactly the same (<span class="tlid-translation translation"><span title="">same data and same parameters)</span></span>?</span> <span title="">It happens to me every time I do it. What can I be doing wrong?</span><br><br><span class="tlid-translation translation"><span title="">Here I leave the example of my code: <span class="tlid-translation translation"><span title="">135 individuals with 8 loci sampled in 6 different locations</span></span></span></span></span></span></span></span></span></strong><br><br><strong>perca <-read.structure("PercaPopName.str",<br>
                                                     onerowperind=TRUE,<br>
                                                     n.ind=135,<br>
                                                     n.loc=8,<br>
                                                     col.lab=1,<br>
                                                     col.pop=2,<br>
                                                     row.marknames=1,<br>
                                                     ask=FALSE)<br><br>
                perca_grp6 <-find.clusters(perca, max.n.clust = 10)<br>
                200<br>
                6<br><br>
                dapc6 <-dapc(perca, perca_grp6$grp)<br>
                200<br>
                5<br><br>
                scatter(dapc6)</strong><br><br><strong>Thank you.</strong><br><br><br><br><br><br>
                Hi, my name is Helena,<br><br><span class="tlid-translation translation"><span title="">I have a question about my DAPC analayses.<br><br><span class="tlid-translation translation"><span title="">I'm following the tutorial step by step and well, I get the DAPC graph of my data, but the problem is that when I repeat this my graphic results come out completely different, therefore they are not reliable...</span><br><span title="">My question is, why do such different results come out if I'm repeating exactly the same?</span> <span title="">It happens to me every time I do it. What can I be doing wrong?</span><br><br><span title="">Here my code:</span></span><br><br>
                perca <-read.structure("PercaPopName.str",<br>
                                                      onerowperind=TRUE,<br>
                                                      n.ind=135,<br>
                                                      n.loc=8,<br>
                                                      col.lab=1,<br>
                                                      col.pop=2,<br>
                                                      row.marknames=1,<br>
                                                      ask=FALSE)<br><br>
                dapc1 <-dapc(perca, perca_grp$grp)<br><br>
                200<br>
                6<br><br>
                scatter(dapc1)</span></span></span></span><br><br><br><strong>Hello again, I`m Helena, sorry but I introduced my code wrong yesterday:<br><br>
                This is my code: </strong><br><br><strong>perca <-read.structure("PercaPopName.str",<br>
                                                     onerowperind=TRUE,<br>
                                                     n.ind=135,<br>
                                                     n.loc=8,<br>
                                                     col.lab=1,<br>
                                                     col.pop=2,<br>
                                                     row.marknames=1,<br>
                                                     ask=FALSE)<br><br>
                perca_grp6 <-find.clusters(perca, max.n.clust = 10)<br>
                200<br>
                6<br><br>
                dapc6 <-dapc(perca, perca_grp6$grp)<br>
                200<br>
                5<br><br>
                scatter(dapc6)<br><br>
                Thank you </strong><br>
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