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Dear adegenet developers and users,<br>
<br>
I have a dataset with 50 individuals across 5 sampling locations in
a microsatellite dataset, and roughly equivalent numbers of
individuals in a SNP dataset with 3839 loci.<br>
I have just been interested in finding whether there is any
population structure in my species. However, when I run the
different datasets I get different answers, and some of them look
strange. <br>
<br>
microsatellite dataset. <br>
Fst, mantel test for IBD and STRUCTURE both find zero evidence of
structure...<br>
<br>
find.clusters says k=4 or 5<br>
then I run optima.a.score and xvalDapc to find the best number of
PCs to retain for a dapc, and I have nice groups in the final
answer, with apparently good assignment power back to the original
groups. <br>
However, my alpha scores for that dapc run is as follows<br>
1 2 3 4 <br>
0.4905714 0.5570149 0.7075510 0.5962500 <br>
<br>
Further, when I visualise this as a compoplot there is no evidence
that these structures actually represent any kind of geographic
structure in the data, as the groups are just randomly dispersed
through my individuals. <br>
<br>
I have read on topics in the forums that if there is enough space in
the data it will find an optimal clustering solution, no matter
whether it is biologically realistic. I have also read that
find.clusters shouldn't find an optimal solution for k=1 because it
is meant to be a non-sense solution for a cluster. Indeed this makes
sense because when you use sampling locality as a prior in dapc it
all comes out as one big cluster.<br>
<br>
HOWEVER, when I run my SNP dataset things get really strange. <br>
<br>
I ran essentially all the same procedures and I've come up against a
number of hurdles:<br>
<br>
1. I can't get the xvalDapc to work on a genlight object. I keep
getting an error: <br>
<br>
Error in as.data.frame.default(x[[i]], optional = TRUE) : <br>
cannot coerce class "structure("SNPbin", package = "adegenet")" to a
data.frame<br>
In addition: Warning message:<br>
In min(dim(x)) : no non-missing arguments to min; returning Inf<br>
<br>
Obviously this is because genlight doesn't store the genetic data in
the same way as the genind objects do. Is there a work around for
using this function?<br>
<br>
So far I have got xvalDapc to work on my genind objects, but I do
get a bunch of "warning messages "49: In if (result == "overall") {
... :<br>
the condition has length > 1 and only the first element will be
used", but it seems to spit out an output at least....<br>
<br>
2. when I run find.clusters my cumulative variance plot is nearly
linear... as is my BICvsK plot, with the optimal solution being the
supposedly non-sensical k=1 (see the attached pdf of the output)? Is
there something weird with my data? Or, is that the genuine signal
coming through? When I use other clustering methods such as
fastSTRUCTURE and mds I don't get any indication of structure
either. HOWEVER, I don't know how to reconcile the two clustering
solutions from the two nuclear data sources.<br>
<br>
3. When I run an a.score analysis it is basically a flat line, and
although it finds an "optimal" pca retention it doesn't seem very
reliable to me (see also attached)<br>
<br>
<br>
<br>
So I am aware that there are a few problems there, but hopefully the
itemisation and the context of my questions help any good hearted
helping people out there. <br>
<br>
Sincerely,<br>
<br>
Peri<br>
<br>
<div class="moz-signature">-- <br>
<b>Peri Bolton</b>
<br>
PhD Candidate, <a
href="http://bio.mq.edu.au/avianbehaviouralecology/"> Griffith
Lab </a>
<br>
Department of Biological Sciences
<br>
Macquarie University, NSW 2109, Australia
<br>
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