<div dir="ltr">Hi Melanie, <div><br></div><div>it's quite hard to tell without seeing the data, but yes, my suspicion is the same as yours, NAs are the culprits. Entirely non-typed loci are normally removed from genind objects during their construction, but it is still possible that for some groups in your data, some loci are entirely missing. </div><div><br></div><div>Given how many SNPs you have, you can probably afford to remove loci with many missing data (just make sure you don't end up throwing too much away). propTyped(..., by = "loc") may be your friend here. Here's an example using microbov:</div><div><br></div><div><br></div><div><div>> data(microbov)</div><div><br></div><div>> propTyped(microbov, by = "loc")</div><div>  INRA63   INRA5   ETH225   ILSTS5    HEL5    HEL1   INRA35   ETH152 </div><div>0.9914773 0.9786932 0.9914773 0.9673295 0.9786932 0.9914773 0.9829545 0.9573864 </div><div>  INRA23   ETH10    HEL9   CSSM66   INRA32    ETH3   BM2113   BM1824 </div><div>0.9644886 0.9943182 0.9701705 0.9886364 0.9687500 0.9829545 0.9914773 0.9900568 </div><div>  HEL13   INRA37   BM1818   ILSTS6    MM12   CSRM60   ETH185   HAUT24 </div><div>0.9772727 0.9815341 0.9588068 0.9446023 0.9744318 0.9730114 0.9275568 0.9872159 </div><div>  HAUT27  TGLA227  TGLA126  TGLA122   TGLA53   SPS115 </div><div>0.9914773 0.9914773 0.9914773 0.9914773 0.9531250 0.9701705 </div><div><br></div><div>> to_keep <-  propTyped(microbov, by = "loc") > .99  # i.e. less 1% missing data </div><div><br></div><div>> to_keep<br></div><div> INRA63  INRA5  ETH225  ILSTS5   HEL5   HEL1  INRA35  ETH152  INRA23  ETH10 </div><div>  TRUE  FALSE   TRUE  FALSE  FALSE   TRUE  FALSE  FALSE  FALSE   TRUE </div><div>  HEL9  CSSM66  INRA32   ETH3  BM2113  BM1824  HEL13  INRA37  BM1818  ILSTS6 </div><div> FALSE  FALSE  FALSE  FALSE   TRUE   TRUE  FALSE  FALSE  FALSE  FALSE </div><div>  MM12  CSRM60  ETH185  HAUT24  HAUT27 TGLA227 TGLA126 TGLA122  TGLA53  SPS115 </div><div> FALSE  FALSE  FALSE  FALSE   TRUE   TRUE   TRUE   TRUE  FALSE  FALSE </div><div><br></div><div>> x <- microbov[loc = to_keep]</div><div><br></div><div>> nLoc(x)</div><div>[1] 10</div><div><br></div><div>> nLoc(microbov)</div><div>[1] 30</div><div><br></div></div><div><br></div><div>This is just an illustration - this dataset actually has little in terms of missing data. In your case you probably want to play with the threshold (99% non-NA is likely an overkill). </div><div><br></div><div>Cheers</div><div>Thibaut</div><div>  </div></div><div class="gmail_extra"><br clear="all"><div><div class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><div><div><br>--<br>Dr Thibaut Jombart</div><div style="font-size:small">Lecturer, Department of Infectious Disease Epidemiology, Imperial College London</div></div><div><span style="font-size:12.8px">Head of RECON: </span><span style="font-size:12.8px"><a href="http://repidemicsconsortium.org" target="_blank">repidemicsconsortium.org</a></span><br></div></div><div><a href="http://sites.google.com/site/thibautjombart/" style="font-size:12.8px" target="_blank">sites.google.com/site/thibautjombart/</a><br></div><div><a href="http://github.com/thibautjombart" target="_blank">github.com/thibautjombart</a></div>Twitter: <a href="http://twitter.com/TeebzR" target="_blank">@TeebzR</a><br></div><div dir="ltr">+44(0)20 7594 3658</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
<br><div class="gmail_quote">On 8 February 2017 at 11:14, Melanie Montes <span dir="ltr"><<a href="mailto:melaniesmontes@gmail.com" target="_blank">melaniesmontes@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div style="font-size:12.8px">Hello all, </div><div style="font-size:12.8px">I recently finished running fstat on my dataset of about 50 000 snps / 56 individuals, and successfully got f-statistics in return. However, when I tried to run gstat.randtest to see if the structure was significant:</div><div style="font-size:12.8px"><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">fstat.sig <-gstat.randtest(nr2014, nsim=1000)</font></span></p></div><div style="font-size:12.8px">...I got 50+ warnings like this:</div><div style="font-size:12.8px"><font face="monospace, monospace"><br></font></div><div style="font-size:12.8px"><font face="monospace, monospace">50: In max(y, na.rm = TRUE) : no non-missing arguments to max; returning -Inf</font><br></div><div style="font-size:12.8px"><br></div><div style="font-size:12.8px">and my results file looked like this:</div><div style="font-size:12.8px"><br></div><div style="font-size:12.8px"><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">> fstat.sig                   </font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">Monte-Carlo test</font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">Call: gstat.randtest(x = nr2014, nsim = 1000)</font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">Observation: 0 </font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">Based on 1000 replicates</font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><font face="monospace, monospace">Simulated p-value: 1 </font></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1"><br></span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1">which leads me to suspect that it did not work. Does this have something to do with the missing data in my dataset? Sorry if this is a naive question, I am an R novice. </span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1">Thanks for your time and the awesome package, I've been using it a lot! </span></p><p class="m_-628742087000702720gmail-m_-6642637731580746140gmail-p1"><span class="m_-628742087000702720gmail-m_-6642637731580746140gmail-s1">Sincerely, </span></p></div><span class="HOEnZb"><font color="#888888"><div><div class="m_-628742087000702720gmail_signature"><div dir="ltr"><span style="font-size:12.8px">Melanie</span></div></div></div>
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