<div dir="ltr"><div class="gmail_default" style="font-size:large;color:#0000ff">Hello,</div><div class="gmail_default" style="font-size:large;color:#0000ff"><br></div><div class="gmail_default" style="font-size:large;color:#0000ff">I am writing to follow-up on my post to the forum from a couple weeks ago, and then my follow-up to that. If the text below does not show up, click on the hidden text, since I just replied to my last email to generate this post.</div><div class="gmail_extra"><div class="gmail_quote"><div><br></div><div> <span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">When trying to find the number of
clusters, as is known, I get different results when I retain different numbers
of PCs.</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"><br></span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">As background, I have samples
from 180 individuals over 11 different sites, and am trying to find the best
structure.</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"><br></span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">In the tutorial, it says that
when you run find.clusters there is no reason for keeping small numbers of
principle components here. When I run with n.pca.max = 60 (so, n/3), using xval
I get pretty consistently that the good number of PCs to retain is 50.</span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"><span></span></p><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"></p><div><img src="cid:ii_jhw59j0m0_163bc0a44a93dc26" width="238" height="212"><br></div></div></div></blockquote><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif"><br></span></div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif">When I run find.cluster using 50
PCs I get anywhere between 7 and 9 clusters, mostly telling the same story for
the data. However, when I run find.cluster with over 100 PCs I consistently get
k = 4 or 5, and the plot is much cleaner. In addition, however, when I look at
my variance explained plots, they don’t really asymptote, either for
find.cluster or for dapc<div class="gmail_default" style="font-size:large;color:rgb(0,0,255);display:inline">.</div></span></div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif"><div class="gmail_default" style="font-size:large;color:rgb(0,0,255);display:inline"><br></div></span></div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif"><div class="gmail_default" style="font-size:large;color:rgb(0,0,255);display:inline"></div></span><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">Both of the variance explained
plots look like</span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"><span></span></p>
<p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"><span><img style="margin-right:0px"></span></p><div><img src="cid:ii_jhw5a9ul1_163bc0acc7ec88ae" width="239" height="212"><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"></span></div></div></div></blockquote><div> </div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">Using the scaled dataset</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"><br></span></div><div><span style="font-size:14.6667px;color:rgb(0,0,255);font-family:Calibri,sans-serif">mat <- scaleGen(Stickle8c10NoOdds, NA.method="mean")</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"><br></span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">I use 120 PCs, and get</span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"><span></span></p>
<div style="color:rgb(0,0,255);font-size:large"><img src="cid:ii_jhw5avww2_163bc0b3d4df2540" width="239" height="212"><span style="font-family:Calibri,sans-serif;font-size:11pt"></span></div></div></div></blockquote><div> <span style="font-family:Calibri,sans-serif;font-size:11pt;color:rgb(0,0,255)">If I run with 90 PCs the number of clusters bumps up to 5, </span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"></p><div><img src="cid:ii_jhw5e9je4_163bc0da5cbb7d20" width="411" height="366"><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"></span></div></div></div></blockquote><div> <span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">However, if I run find.cluster
and choose 50 PCs, I get</span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div><p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;line-height:normal;margin:0cm 0cm 8pt;font-family:Calibri,sans-serif"><span></span></p>
<div style="color:rgb(0,0,255);font-size:large"><img src="cid:ii_jhw5b8k03_163bc0b7c9cb3023" width="239" height="212"><span style="font-family:"Lucida Console";font-size:10pt"></span></div></div></div></blockquote><div> <div class="gmail_default" style="font-size:large;color:rgb(0,0,255);display:inline"></div><span style="font-family:"Lucida Console";font-size:10pt;color:rgb(0,0,255)">> head(NumClust$Kstat,
11)</span></div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>
<p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;margin:0cm 0cm 0.0001pt;line-height:11.25pt;background:white;word-break:break-all;font-family:Calibri,sans-serif"><span style="font-size:10pt;font-family:"Lucida Console";color:black;border:1pt none windowtext;padding:0cm"><span> </span>K=1<span>
</span>K=2<span> </span>K=3<span> </span>K=4<span>
</span>K=5<span> </span>K=6<span> </span>K=7<span>
</span>K=8<span> </span>K=9<span> </span>K=10<span>
</span>K=11 <span></span></span></p>
<p class="MsoNormal" style="color:rgb(0,0,255);font-size:11pt;margin:0cm 0cm 0.0001pt;line-height:11.25pt;background:white;word-break:break-all;font-family:Calibri,sans-serif"><span style="font-size:10pt;font-family:"Lucida Console";color:black;border:1pt none windowtext;padding:0cm">1492.620
1472.790 1455.980 1448.216 1443.735 1442.909 1440.166 1440.344 1440.867
1441.979 1443.101</span></p></div></div></blockquote><div> </div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif">Are the xval procedure results
(i.e., 50 PCs in my case) meant to be used only at the dapc1 <- dapc(mat,
NumClust$grp) stage? And, do my variance explained plots concern you at all
given that they don’t asymptote? </span></div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif"><br></span></div><div><span style="font-size:11pt;color:rgb(0,0,255);font-family:Calibri,sans-serif">I've attached a word document with all the same text and plots as are in this message in case they don't show up on your screen.</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt"><br></span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">Thank you for your time,</span></div><div><span style="color:rgb(0,0,255);font-family:Calibri,sans-serif;font-size:11pt">E<div class="gmail_default" style="font-size:large;color:rgb(0,0,255);display:inline">lla</div></span></div></div>-- <br><div class="m_-3265058768491519903gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div>Ella Bowles, PhD<br>Postdoctoral Researcher<br>Department of Biology<br>Concordia University<br><br>Website: <a href="https://ellabowlesphd.wordpress.com/" target="_blank">https://<wbr>ellabowlesphd.wordpress.com/</a><br>Email: <a href="mailto:bowlese@gmail.com" target="_blank">bowlese@gmail.com</a></div></div></div></div></div></div></div>
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