diff --git a/docs/articles/index.html b/docs/articles/index.html
index 2466648a..d11c2a15 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -96,7 +96,7 @@
       </header>
 
       <div class="page-header">
-  <h1>Articles <small>version&nbsp;2.6.1</small></h1>
+  <h1>Articles <small>version&nbsp;2.7.1</small></h1>
 </div>
 
 <div class="row">
diff --git a/docs/articles/mlg.html b/docs/articles/mlg.html
index 1904d990..7326239d 100644
--- a/docs/articles/mlg.html
+++ b/docs/articles/mlg.html
@@ -5,7 +5,7 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>Analysis of Multilocus Genotypes and Lineages in poppr 2.6.1 • poppr</title>
+<title>Analysis of Multilocus Genotypes and Lineages in poppr 2.7.1 • poppr</title>
 <!-- jquery --><script src="https://code.jquery.com/jquery-3.1.0.min.js" integrity="sha384-nrOSfDHtoPMzJHjVTdCopGqIqeYETSXhZDFyniQ8ZHcVy08QesyHcnOUpMpqnmWq" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-BVYiiSIFeK1dGmJRAkycuHAHRg32OmUcww7on3RYdg4Va+PmSTsz/K68vbdEjh4u" crossorigin="anonymous">
 <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script><!-- Font Awesome icons --><link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-T8Gy5hrqNKT+hzMclPo118YTQO6cYprQmhrYwIiQ/3axmI1hQomh7Ud2hPOy8SP1" crossorigin="anonymous">
 <!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet">
@@ -75,10 +75,10 @@
       </header><div class="row">
   <div class="col-md-9">
     <div class="page-header toc-ignore">
-      <h1>Analysis of Multilocus Genotypes and Lineages in poppr 2.6.1</h1>
+      <h1>Analysis of Multilocus Genotypes and Lineages in poppr 2.7.1</h1>
                         <h4 class="author">Zhian N. Kamvar and Niklaus J. Grünwald</h4>
             
-            <h4 class="date">2018-01-15</h4>
+            <h4 class="date">2018-03-16</h4>
           </div>
 
     
diff --git a/docs/articles/poppr_manual.html b/docs/articles/poppr_manual.html
index 901578f7..df3f17ce 100644
--- a/docs/articles/poppr_manual.html
+++ b/docs/articles/poppr_manual.html
@@ -5,7 +5,7 @@
 <meta charset="utf-8">
 <meta http-equiv="X-UA-Compatible" content="IE=edge">
 <meta name="viewport" content="width=device-width, initial-scale=1.0">
-<title>Data import and manipulation in poppr version 2.6.1 • poppr</title>
+<title>Data import and manipulation in poppr version 2.7.1 • poppr</title>
 <!-- jquery --><script src="https://code.jquery.com/jquery-3.1.0.min.js" integrity="sha384-nrOSfDHtoPMzJHjVTdCopGqIqeYETSXhZDFyniQ8ZHcVy08QesyHcnOUpMpqnmWq" crossorigin="anonymous"></script><!-- Bootstrap --><link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-BVYiiSIFeK1dGmJRAkycuHAHRg32OmUcww7on3RYdg4Va+PmSTsz/K68vbdEjh4u" crossorigin="anonymous">
 <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script><!-- Font Awesome icons --><link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-T8Gy5hrqNKT+hzMclPo118YTQO6cYprQmhrYwIiQ/3axmI1hQomh7Ud2hPOy8SP1" crossorigin="anonymous">
 <!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet">
@@ -75,10 +75,10 @@
       </header><div class="row">
   <div class="col-md-9">
     <div class="page-header toc-ignore">
-      <h1>Data import and manipulation in poppr version 2.6.1</h1>
+      <h1>Data import and manipulation in poppr version 2.7.1</h1>
                         <h4 class="author">Zhian N. Kamvar and Niklaus J. Grünwald</h4>
             
-            <h4 class="date">2018-01-15</h4>
+            <h4 class="date">2018-03-16</h4>
           </div>
 
     
@@ -135,7 +135,7 @@ <h2 class="hasAnchor">
 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">citation</span>(<span class="dt">package =</span> <span class="st">"poppr"</span>)</code></pre></div>
 <pre><code>## 
 ## To cite poppr in publications or presentations, please specify
-## poppr version 2.6.1 and with the following citation:
+## poppr version 2.7.1 and with the following citation:
 ## 
 ##   Kamvar ZN, Tabima JF, Grünwald NJ. (2014) Poppr: an R package
 ##   for genetic analysis of populations with clonal, partially
@@ -201,12 +201,12 @@ <h2 class="hasAnchor">
 <pre><code>## Loading required package: adegenet</code></pre>
 <pre><code>## Loading required package: ade4</code></pre>
 <pre><code>## 
-##    /// adegenet 2.1.0 is loaded ////////////
+##    /// adegenet 2.1.1 is loaded ////////////
 ## 
 ##    &gt; overview: '?adegenet'
 ##    &gt; tutorials/doc/questions: 'adegenetWeb()' 
 ##    &gt; bug reports/feature requests: adegenetIssues()</code></pre>
-<pre><code>## This is poppr version 2.6.1. To get started, type package?poppr
+<pre><code>## This is poppr version 2.7.1. To get started, type package?poppr
 ## OMP parallel support: available</code></pre>
 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/getfile.html">getfile</a></span>()</code></pre></div>
 <p>A pop up window will appear like this<a href="#fn1" class="footnoteRef" id="fnref1"><sup>1</sup></a>:</p>
@@ -1655,13 +1655,13 @@ <h2 class="hasAnchor">
 <p>This allows you to produce publication quality graphs directly in R. Please see Hadley Wickham“s <em>ggplot2</em> package for more details <span class="citation">(Wickham 2009)</span>. Note that if you don”t like using <em>ggplot2</em>, you can access the data in the ggplot2 object and plot the data yourself:</p>
 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">head</span>(p<span class="op">$</span>data)</code></pre></div>
 <pre><code>## # A tibble: 6 x 4
-##   Population MLG    count order 
-##   &lt;fctr&gt;     &lt;chr&gt;  &lt;int&gt; &lt;fctr&gt;
-## 1 Athena     MLG.20     9 1     
-## 2 Athena     MLG.66     5 2     
-## 3 Athena     MLG.14     3 3     
-## 4 Athena     MLG.35     3 4     
-## 5 Athena     MLG.13     2 5     
+##   Population MLG    count order
+##   &lt;fct&gt;      &lt;chr&gt;  &lt;int&gt; &lt;fct&gt;
+## 1 Athena     MLG.20     9 1    
+## 2 Athena     MLG.66     5 2    
+## 3 Athena     MLG.14     3 3    
+## 4 Athena     MLG.35     3 4    
+## 5 Athena     MLG.13     2 5    
 ## 6 Athena     MLG.16     2 6</code></pre>
 </div>
 <div id="appendix:graphics" class="section level2">
diff --git a/docs/authors.html b/docs/authors.html
index d3edfd49..22222878 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -170,6 +170,10 @@ <h1>Authors</h1>
         <p><strong>Brian J. Knaus</strong>. Contributor.
         <br /><small>0000-0003-1665-4343</small></p>
       </li>
+      <li>
+        <p><strong>Patrick G. Meirmans</strong>. Contributor.
+        <br /><small>0000-0002-6395-8107</small></p>
+      </li>
       <li>
         <p><strong>Niklaus J. Grunwald</strong>. Thesis advisor.
         <br /><small>0000-0003-1656-7602</small></p>
diff --git a/docs/index.html b/docs/index.html
index 419ff74e..a8401249 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -206,11 +206,11 @@ <h3 class="hasAnchor">
 </tr>
 <tr class="even">
 <td align="left">Data import and manipulation</td>
-<td align="left"><code><a href="https://cran.rstudio.com/web/packages/poppr/vignettes/poppr_manual.html">vignette("poppr_manual", "poppr")</a></code></td>
+<td align="left"><code>vignette("poppr_manual", "poppr")</code></td>
 </tr>
 <tr class="odd">
 <td align="left">Multilocus Genotype Analysis</td>
-<td align="left"><code><a href="https://cran.rstudio.com/web/packages/poppr/vignettes/mlg.html">vignette("mlg", "poppr")</a></code></td>
+<td align="left"><code>vignette("mlg", "poppr")</code></td>
 </tr>
 </tbody>
 </table>
@@ -261,8 +261,9 @@ <h2>Developers</h2>
 </ul>
 <h2>Dev status</h2>
 <ul class="list-unstyled">
-<li><a href="https://travis-ci.org/grunwaldlab/poppr"><img src="https://travis-ci.org/grunwaldlab/poppr.svg?branch=master" alt="Build Status"></a></li>
-<li><a href="https://coveralls.io/r/grunwaldlab/poppr?branch=master"><img src="https://coveralls.io/repos/grunwaldlab/poppr/badge.svg?branch=master" alt="Coverage Status"></a></li>
+<li><a href="https://travis-ci.org/grunwaldlab/poppr"><img src="https://travis-ci.org/grunwaldlab/poppr.svg?branch=update-amova" alt="Build Status"></a></li>
+<li><a href="https://ci.appveyor.com/project/grunwaldlab/poppr"><img src="https://ci.appveyor.com/api/projects/status/github/grunwaldlab/poppr?branch=master&amp;svg=true" alt="AppVeyor build status"></a></li>
+<li><a href="https://coveralls.io/r/grunwaldlab/poppr?branch=update-amova"><img src="https://coveralls.io/repos/grunwaldlab/poppr/badge.svg?branch=update-amova" alt="Coverage Status"></a></li>
 <li><a href="https://cran.r-project.org/package=poppr"><img src="http://www.r-pkg.org/badges/version/poppr" alt="CRAN version"></a></li>
 </ul>
 </div>
diff --git a/docs/news/index.html b/docs/news/index.html
index f4d486ed..af49df97 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -103,6 +103,51 @@ <h1>Change log <small>All releases</small></h1>
     </div>
 
     <div class="contents">
+    <div id="poppr-2-7-1" class="section level1">
+<h1 class="hasAnchor">
+<a href="#poppr-2-7-1" class="anchor"></a>poppr 2.7.1</h1>
+<div id="misc" class="section level2">
+<h2 class="hasAnchor">
+<a href="#misc" class="anchor"></a>MISC</h2>
+<ul>
+<li>Missing documentation for <code><a href="../reference/poppr.amova.html">poppr.amova()</a></code> has been added.</li>
+<li>Polysat is now listed in imports.</li>
+</ul>
+</div>
+</div>
+    <div id="poppr-2-7-0" class="section level1">
+<h1 class="hasAnchor">
+<a href="#poppr-2-7-0" class="anchor"></a>poppr 2.7.0</h1>
+<div id="new-functions" class="section level2">
+<h2 class="hasAnchor">
+<a href="#new-functions" class="anchor"></a>NEW FUNCTIONS</h2>
+<ul>
+<li><p><code><a href="../reference/make_haplotypes.html">make_haplotypes()</a></code> will split your data into pseudo-haplotypes for use in AMOVA-like analyses. This was a previously internal function, but has been promoted to a user-facing function in this version.</p></li>
+<li><p><code><a href="../reference/coercion-methods.html">as.genambig()</a></code> will convert genind/genclone objects to Polysat’s “genambig” class. Note that polysat must be installed for this to work.</p></li>
+</ul>
+</div>
+<div id="algorithmic-change" class="section level2">
+<h2 class="hasAnchor">
+<a href="#algorithmic-change" class="anchor"></a>ALGORITHMIC CHANGE</h2>
+<ul>
+<li>AMOVA will now default to using euclidean distance. This affects all calculations made with <code>within = FALSE</code> or <code>filter = TRUE</code> without a user-supplied distance. This will not have affect those with haploid or diploid data using <code>within = TRUE</code>. The dissimilarity distance is equivalent to a squared euclidean distance for haploid genotypes, but not for any higher ploidy. Those using <code>filter = TRUE</code> without specifying a distance should use a euclidean threshold. This should not be an issue for those who simply want to group isolates with missing data, however as a zero distance is the same for euclidean and dissimilarity. Thanks goes to Patrick Meirmans for alerting me to this error.</li>
+</ul>
+</div>
+<div id="new-features" class="section level2">
+<h2 class="hasAnchor">
+<a href="#new-features" class="anchor"></a>NEW FEATURES</h2>
+<ul>
+<li>AMOVA will now calculate within-individual variance for polyploid data.</li>
+</ul>
+</div>
+<div id="misc-1" class="section level2">
+<h2 class="hasAnchor">
+<a href="#misc-1" class="anchor"></a>MISC</h2>
+<ul>
+<li>printing of AMOVA will now better handle any changes in methods from pegas or ade4.</li>
+</ul>
+</div>
+</div>
     <div id="poppr-2-6-1" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-6-1" class="anchor"></a>poppr 2.6.1</h1>
@@ -117,16 +162,16 @@ <h2 class="hasAnchor">
     <div id="poppr-2-6-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-6-0" class="anchor"></a>poppr 2.6.0</h1>
-<div id="new-functions" class="section level2">
+<div id="new-functions-1" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-1" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>The new function <code><a href="../reference/boot.ia.html">boot.ia()</a></code> is conceptually similar to <code><a href="../reference/ia.html">resample.ia()</a></code>, except it resamples with replacement.</li>
 </ul>
 </div>
-<div id="new-features" class="section level2">
+<div id="new-features-1" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-1" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>The function <code><a href="../reference/ia.html">resample.ia()</a></code> now can resample individuals weighted by their Psex value.</li>
 <li>The minimum spanning networks will now scale nodes by area instead of radius. This gives a more accurate picture of the differences between MLGs. See <a href="https://github.com/grunwaldlab/poppr/issues/154" class="uri">https://github.com/grunwaldlab/poppr/issues/154</a> for details.</li>
@@ -152,9 +197,9 @@ <h2 class="hasAnchor">
 <li>The minimum version of igraph has been set to 1.0.0.</li>
 </ul>
 </div>
-<div id="misc" class="section level2">
+<div id="misc-2" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc" class="anchor"></a>MISC</h2>
+<a href="#misc-2" class="anchor"></a>MISC</h2>
 <ul>
 <li>The MSN is now plotted last in <code><a href="../reference/plot_poppr_msn.html">plot_poppr_msn()</a></code> so additional legends can be added if necessary.</li>
 </ul>
@@ -163,9 +208,9 @@ <h2 class="hasAnchor">
     <div id="poppr-2-5-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-5-0" class="anchor"></a>poppr 2.5.0</h1>
-<div id="algorithmic-change" class="section level2">
+<div id="algorithmic-change-1" class="section level2">
 <h2 class="hasAnchor">
-<a href="#algorithmic-change" class="anchor"></a>ALGORITHMIC CHANGE</h2>
+<a href="#algorithmic-change-1" class="anchor"></a>ALGORITHMIC CHANGE</h2>
 <ul>
 <li>Identified in <a href="https://github.com/grunwaldlab/poppr/issues/139" class="uri">https://github.com/grunwaldlab/poppr/issues/139</a>, Bruvo’s distance will now consider all possible combinations of ordered alleles in the calculation under the genome addition and loss models for missing data. This will affect those who have polyploid data that contain more than one missing allele at any genotype</li>
 </ul>
@@ -187,9 +232,9 @@ <h2 class="hasAnchor">
 <li>A bug in read.genalex() where removed samples would have incorrect strata labels was fixed. Thanks to Hernán Dario Capador-Barreto for identifying it. See <a href="https://github.com/grunwaldlab/poppr/issues/147" class="uri">https://github.com/grunwaldlab/poppr/issues/147</a>.</li>
 </ul>
 </div>
-<div id="misc-1" class="section level2">
+<div id="misc-3" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-1" class="anchor"></a>MISC</h2>
+<a href="#misc-3" class="anchor"></a>MISC</h2>
 <ul>
 <li>The internal plotting function for mlg.table now uses tidy evaluation for dplyr versions &gt; 0.5.0</li>
 <li>The package reshape2 was removed from imports and replaced with base functions (see <a href="https://github.com/grunwaldlab/poppr/issues/144" class="uri">https://github.com/grunwaldlab/poppr/issues/144</a> for details)</li>
@@ -218,17 +263,17 @@ <h2 class="hasAnchor">
     <div id="poppr-2-4-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-4-0" class="anchor"></a>poppr 2.4.0</h1>
-<div id="new-functions-1" class="section level2">
+<div id="new-functions-2" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-1" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-2" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code><a href="../reference/ia.html">jack.ia()</a></code> will randomly jackknife your sample to a specified n (default is the number of MLG), and calculate the index of association over multiple iterations, giving a distribution of possible values at a given sample size.</li>
 </ul>
 </div>
-<div id="new-features-1" class="section level2">
+<div id="new-features-2" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-1" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-2" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>The function <code><a href="../reference/mlg.html">mlg.table()</a></code> gains new parameters, “color” and “background”. The “color” parameter will create a single barplot with colors representing populations while the “background” parameter will create a background plot showing the abundance of MLGs across populations within the facets.</li>
 <li>The function <code><a href="../reference/win.ia.html">win.ia()</a></code> will now take into consideration chromosomal coordinates when constructing windows. It has additionally acquired a new parameter <code>chromosome_buffer</code>, which allows the user to specify whether or not the window should be limited to within chromosomes.</li>
@@ -262,9 +307,9 @@ <h2 class="hasAnchor">
 <li>PROTECT statements were placed around allocation statements. For details, see <a href="https://github.com/grunwaldlab/poppr/issues/133" class="uri">https://github.com/grunwaldlab/poppr/issues/133</a>.</li>
 </ul>
 </div>
-<div id="misc-2" class="section level2">
+<div id="misc-4" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-2" class="anchor"></a>MISC</h2>
+<a href="#misc-4" class="anchor"></a>MISC</h2>
 <ul>
 <li>The documentation for <code><a href="../reference/bitwise.dist.html">bitwise.dist()</a></code> clarifies the role of the <code>differences_only</code> flag (see <a href="https://github.com/grunwaldlab/poppr/issues/119" class="uri">https://github.com/grunwaldlab/poppr/issues/119</a>).</li>
 <li>Interruptions in C code is now handled gracefully via <code>R_CheckUserInterrupt()</code>. The benefit is that long-running calculations are interrupted near instantly, but at the cost of a few more milliseconds of computation time. (see <a href="https://github.com/grunwaldlab/poppr/issues/86" class="uri">https://github.com/grunwaldlab/poppr/issues/86</a>)</li>
@@ -275,26 +320,26 @@ <h2 class="hasAnchor">
     <div id="poppr-2-3-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-3-0" class="anchor"></a>poppr 2.3.0</h1>
-<div id="new-functions-2" class="section level2">
+<div id="new-functions-3" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-2" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-3" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>The function <code><a href="../reference/coercion-methods.html">bootgen2genind()</a></code> will help users take advantage of bootstrapping distance functions from other packages that require genind objects. For details, see <a href="https://github.com/grunwaldlab/poppr/issues/112" class="uri">https://github.com/grunwaldlab/poppr/issues/112</a> and <a href="https://github.com/grunwaldlab/poppr/issues/111" class="uri">https://github.com/grunwaldlab/poppr/issues/111</a>
 </li>
 </ul>
 </div>
-<div id="new-features-2" class="section level2">
+<div id="new-features-3" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-2" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-3" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>There is now a <code>plot</code> parameter for the genotype curve to enable or suppress plotting.</li>
 <li>Progress bars are now automatically suppressed when running non-interactively. to turn them on when running non-interactively, use <code>options(poppr.debug = TRUE)</code>.</li>
 <li>The progress bar for <code><a href="../reference/ia.html">ia()</a></code> and <code><a href="../reference/poppr.html">poppr()</a></code> will now show estimated time. This is from dplyr’s <code>progress_estimated()</code>.</li>
 </ul>
 </div>
-<div id="misc-3" class="section level2">
+<div id="misc-5" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-3" class="anchor"></a>MISC</h2>
+<a href="#misc-5" class="anchor"></a>MISC</h2>
 <ul>
 <li>The <code>hist</code> argument in the <code><a href="../reference/ia.html">ia()</a></code> is deprecated in favor of <code>plot</code>.</li>
 <li>The x axis for the <code><a href="../reference/genotype_curve.html">genotype_curve()</a></code> plot is now numeric, allowing you to fit a smoothing function over the points without having to use the hack <code>geom_smooth(aes(group = 1))</code>. This is thanks to Kara Woo for pointing this out on twitter (<a href="https://twitter.com/kara_woo/status/783336540407685120" class="uri">https://twitter.com/kara_woo/status/783336540407685120</a>).</li>
@@ -325,18 +370,18 @@ <h2 class="hasAnchor">
 </li>
 </ul>
 </div>
-<div id="new-features-3" class="section level2">
+<div id="new-features-4" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-3" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-4" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>You can now specify layout parameters in <code><a href="../reference/imsn.html">imsn()</a></code>
 </li>
 <li>The *.msn functions will now take into account whether or not your data is set to collapsed MLGs. (see <a href="https://github.com/grunwaldlab/poppr/issues/107" class="uri">https://github.com/grunwaldlab/poppr/issues/107</a>)</li>
 </ul>
 </div>
-<div id="misc-4" class="section level2">
+<div id="misc-6" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-4" class="anchor"></a>MISC</h2>
+<a href="#misc-6" class="anchor"></a>MISC</h2>
 <ul>
 <li>Errors from mlg.filter now make more sense. (see <a href="https://github.com/grunwaldlab/poppr/issues/109" class="uri">https://github.com/grunwaldlab/poppr/issues/109</a>)</li>
 <li>The vignette poppr_manual has been converted to HTML format. (see <a href="https://github.com/grunwaldlab/poppr/issues/113" class="uri">https://github.com/grunwaldlab/poppr/issues/113</a>)</li>
@@ -346,17 +391,17 @@ <h2 class="hasAnchor">
     <div id="poppr-2-2-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-2-0" class="anchor"></a>poppr 2.2.0</h1>
-<div id="new-functions-3" class="section level2">
+<div id="new-functions-4" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-3" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-4" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code><a href="../reference/incomp.html">incomp()</a></code> will check your data to see if there are any incomparable samples.</li>
 </ul>
 </div>
-<div id="new-features-4" class="section level2">
+<div id="new-features-5" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-4" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-5" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>Threshold argument added to <code><a href="../reference/filter_stats.html">filter_stats()</a></code> (see <a href="https://github.com/grunwaldlab/poppr/issues/94" class="uri">https://github.com/grunwaldlab/poppr/issues/94</a>)</li>
 <li>The pipe operator (<code>%&gt;%</code>) is now exported from magrittr to make chaining commands easier.</li>
@@ -381,9 +426,9 @@ <h2 class="hasAnchor">
 <li>An issue where <code><a href="../reference/mll.reset-method.html">mll.reset()</a></code> did not reset non-MLG class objects in the mlg slot was fixed.</li>
 </ul>
 </div>
-<div id="misc-5" class="section level2">
+<div id="misc-7" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-5" class="anchor"></a>MISC</h2>
+<a href="#misc-7" class="anchor"></a>MISC</h2>
 <ul>
 <li>Documentation for <code><a href="../reference/mlg.filter.html">mlg.filter()</a></code> was clarified and updated with more examples.</li>
 <li>The vignette “Migration from poppr version 1” has been removed.</li>
@@ -394,9 +439,9 @@ <h2 class="hasAnchor">
     <div id="poppr-2-1-1" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-2-1-1" class="anchor"></a>poppr 2.1.1</h1>
-<div id="new-features-5" class="section level2">
+<div id="new-features-6" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-5" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-6" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>
 <code><a href="../reference/imsn.html">imsn()</a></code> now has collapsible side panels</li>
@@ -406,9 +451,9 @@ <h2 class="hasAnchor">
 <code><a href="../reference/rraf.html">rraf()</a></code> now gives options for minor allele correction encompassed in the internal function <code><a href="../reference/rare_allele_correction.html">rare_allele_correction()</a></code>. This extends also to <code><a href="../reference/pgen.html">pgen()</a></code> and <code><a href="../reference/psex.html">psex()</a></code>, which must correct minor allele frequencies by default. See <a href="https://github.com/grunwaldlab/poppr/issues/81" class="uri">https://github.com/grunwaldlab/poppr/issues/81</a> for details.</li>
 </ul>
 </div>
-<div id="misc-6" class="section level2">
+<div id="misc-8" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-6" class="anchor"></a>MISC</h2>
+<a href="#misc-8" class="anchor"></a>MISC</h2>
 <ul>
 <li>
 <code><a href="../reference/mlg.filter.html">mlg.filter()</a></code> now defaults to using <code><a href="../reference/diss.dist.html">diss.dist()</a></code>
@@ -449,9 +494,9 @@ <h2 class="hasAnchor">
 <li>The internal code for the <code>genotype_curve</code> has been implemented in C for a 10x increase in speed.</li>
 </ul>
 </div>
-<div id="new-features-6" class="section level2">
+<div id="new-features-7" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-6" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-7" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>
 <code>poppr.msn</code>, <code>bruvo.msn</code>, and <code>plot_poppr_msn</code> gain the ability to take character vectors for color palettes. See issue #55 (<a href="https://github.com/grunwaldlab/poppr/issues/55" class="uri">https://github.com/grunwaldlab/poppr/issues/55</a>) for details.</li>
@@ -475,9 +520,9 @@ <h2 class="hasAnchor">
 <code>poppr.amova</code> can now perform amova using the pegas implementation.</li>
 </ul>
 </div>
-<div id="new-functions-4" class="section level2">
+<div id="new-functions-5" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-4" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-5" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code>rrmlg</code> will calculate round-robin multilocus genotypes for each locus.</li>
@@ -496,9 +541,9 @@ <h2 class="hasAnchor">
 <li>because we’re through being cool.</li>
 </ul>
 </div>
-<div id="misc-7" class="section level2">
+<div id="misc-9" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-7" class="anchor"></a>MISC</h2>
+<a href="#misc-9" class="anchor"></a>MISC</h2>
 <ul>
 <li>Documentation for genclone and snpclone classes are more coherent.</li>
 <li>Accessors added for internal MLG objects (for developers).</li>
@@ -546,9 +591,9 @@ <h2 class="hasAnchor">
 <code>read.genealex</code> can now correctly import missing data for diploids (issue #42)</li>
 </ul>
 </div>
-<div id="new-features-7" class="section level2">
+<div id="new-features-8" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-7" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-8" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>Startup message now tells you if poppr was compiled with OMP support.</li>
 </ul>
@@ -593,9 +638,9 @@ <h2 class="hasAnchor">
 <li>refreshing!</li>
 </ul>
 </div>
-<div id="new-features-8" class="section level2">
+<div id="new-features-9" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-8" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-9" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>The default plot for the index of association will now be a single histogram. The user has the option to visualize the standardized index of association (<code>index = "rbarD"</code>, default) or the classic index of association (<code>index =   "Ia"</code>). If the user uses the function <code>ia</code> with the argument <code>valuereturn =   TRUE</code>, then the resulting object can be plotted with the plot function.</li>
 <li>The function <code>poppr</code> will now plot all populations in a single faceted plot instead of one plot per population.</li>
@@ -624,9 +669,9 @@ <h2 class="hasAnchor">
 <code>genind2genalex</code> gains the ability to selectively write different strata.</li>
 </ul>
 </div>
-<div id="new-functions-5" class="section level2">
+<div id="new-functions-6" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-5" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-6" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code>mlg.filter</code> will contract multilocus genotypes given a genetic distance and threshold using one of three algorithms. It can report statistics such as the multilocus genotypes returned, the number of samples within each multilocus genotype, the thresholds at which multilocus genotypes were collapsed, and the genetic distance matrix that represents the new multilocus genotypes.</li>
@@ -710,9 +755,9 @@ <h2 class="hasAnchor">
     <div id="poppr-1-1-3" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-1-1-3" class="anchor"></a>poppr 1.1.3</h1>
-<div id="new-features-9" class="section level2">
+<div id="new-features-10" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-9" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-10" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>new arguments to <code>plot_poppr_msn</code> to allow for easier manipulation of node sizes and of labeling</li>
 <li>read.genalex can now take read text connections as input. Addresses issue #8</li>
@@ -735,9 +780,9 @@ <h2 class="hasAnchor">
 </li>
 </ul>
 </div>
-<div id="misc-8" class="section level2">
+<div id="misc-10" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-8" class="anchor"></a>MISC</h2>
+<a href="#misc-10" class="anchor"></a>MISC</h2>
 <ul>
 <li>
 <code>info_table</code> will print a discrete scale as opposed to colorbar when type = “ploidy”</li>
@@ -773,9 +818,9 @@ <h2 class="hasAnchor">
     <div id="poppr-1-1-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-1-1-0" class="anchor"></a>poppr 1.1.0</h1>
-<div id="new-features-10" class="section level2">
+<div id="new-features-11" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-10" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-11" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>Polyploids with ambiguous genotypes are now supported in poppr. See documentation for <code>recode_polyploids</code> for details.</li>
 <li>Calculations of Bruvo’s distance now features correction for partial missing data utilizing genome addition and genome loss models as presented in Bruvo et al. 2004.</li>
@@ -800,9 +845,9 @@ <h2 class="hasAnchor">
 <li>The <code>genclone</code> object is a new extension of the <code>genind</code> object from adegenet. This object contains slots containing population hierarchies and multilocus genotype definitions and will work with all analyses in adegenet and poppr.</li>
 </ul>
 </div>
-<div id="new-functions-6" class="section level2">
+<div id="new-functions-7" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-6" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-7" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>[get,set,name,split,add]hierarchy - functions that will manipulate the hierarchy slot in a <code>genclone</code> object utilizing hierarchical formulae as arguments for simplification.</li>
 <li>
@@ -867,9 +912,9 @@ <h2 class="hasAnchor">
 <li>The function <code>poppr</code> will no longer return rounded results, but rather is printed with three significant digits.</li>
 </ul>
 </div>
-<div id="misc-9" class="section level2">
+<div id="misc-11" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-9" class="anchor"></a>MISC</h2>
+<a href="#misc-11" class="anchor"></a>MISC</h2>
 <ul>
 <li>Added unit tests.</li>
 <li>The poppr user manual has been shortened to only include instructions on data manipulation.</li>
@@ -905,9 +950,9 @@ <h2 class="hasAnchor">
 <li>Fixed bug for users who have downloaded ape version 3.1 or higher where bruvo.boot would throw an error.</li>
 </ul>
 </div>
-<div id="misc-10" class="section level2">
+<div id="misc-12" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-10" class="anchor"></a>MISC</h2>
+<a href="#misc-12" class="anchor"></a>MISC</h2>
 <ul>
 <li>Updated citation information.</li>
 </ul>
@@ -939,9 +984,9 @@ <h2 class="hasAnchor">
 <li>Changes to <code>bruvo.boot</code> allow for ever so slightly faster bootstrapping.</li>
 </ul>
 </div>
-<div id="misc-11" class="section level2">
+<div id="misc-13" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-11" class="anchor"></a>MISC</h2>
+<a href="#misc-13" class="anchor"></a>MISC</h2>
 <ul>
 <li>Permutations for I_A and \bar{r}_d are now visualized as a progress bar as opposed to dots.</li>
 </ul>
@@ -959,9 +1004,9 @@ <h2 class="hasAnchor">
 </ul>
 <p>(1994) normalization for NJ trees.</p>
 </div>
-<div id="misc-12" class="section level2">
+<div id="misc-14" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-12" class="anchor"></a>MISC</h2>
+<a href="#misc-14" class="anchor"></a>MISC</h2>
 <ul>
 <li>github repository for poppr has changed from github.com/poppr/poppr to github.com/grunwaldlab/poppr</li>
 </ul>
@@ -978,9 +1023,9 @@ <h2 class="hasAnchor">
 <li>Utilized rmultinom function to increase speed of bootstrap sampling methods for shufflepop and ia.</li>
 </ul>
 </div>
-<div id="new-features-11" class="section level2">
+<div id="new-features-12" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-11" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-12" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>Function <code>informloci</code> will remove phylogenetically uninformative loci.</li>
 </ul>
@@ -1020,9 +1065,9 @@ <h2 class="hasAnchor">
 <li>Expanded installation section to include installation instructions from github.</li>
 </ul>
 </div>
-<div id="misc-13" class="section level2">
+<div id="misc-15" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-13" class="anchor"></a>MISC</h2>
+<a href="#misc-15" class="anchor"></a>MISC</h2>
 <ul>
 <li>internal permutation algorithm no longer lists permutations in reverse order</li>
 </ul>
@@ -1047,9 +1092,9 @@ <h2 class="hasAnchor">
 <li>Input values that are not multiples of the specified repeat length for Bruvo’s distance are now rounded (as opposed to being forced as integers).</li>
 </ul>
 </div>
-<div id="misc-14" class="section level2">
+<div id="misc-16" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-14" class="anchor"></a>MISC</h2>
+<a href="#misc-16" class="anchor"></a>MISC</h2>
 <ul>
 <li>Vignette updated for aesthetics and to reflect algorithmic changes.</li>
 </ul>
@@ -1058,9 +1103,9 @@ <h2 class="hasAnchor">
     <div id="poppr-1-0-0" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-1-0-0" class="anchor"></a>poppr 1.0.0</h1>
-<div id="misc-15" class="section level2">
+<div id="misc-17" class="section level2">
 <h2 class="hasAnchor">
-<a href="#misc-15" class="anchor"></a>MISC</h2>
+<a href="#misc-17" class="anchor"></a>MISC</h2>
 <ul>
 <li>Poppr has been confirmed to work on Linux, Mac, and Windows systems with R 3.0.0.</li>
 <li>Vignette <code>poppr_manual</code> now has cross-references to different sections.</li>
@@ -1078,9 +1123,9 @@ <h2 class="hasAnchor">
     <div id="poppr-0-4-1" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-0-4-1" class="anchor"></a>poppr 0.4.1</h1>
-<div id="new-features-12" class="section level2">
+<div id="new-features-13" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-12" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-13" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>
 <code>getfile</code> has a new argument, “combine”, which will automatically add the path to the list of files, so they can be read without switching working directory.</li>
@@ -1111,9 +1156,9 @@ <h2 class="hasAnchor">
 <code>read.genalex</code> can now correctly recognize regional formatting without an extra column.</li>
 </ul>
 </div>
-<div id="new-features-13" class="section level2">
+<div id="new-features-14" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-13" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-14" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>
 <code>read.genalex</code> will now be able to take in a file that is formatted with both regional and geographic data.</li>
@@ -1156,17 +1201,17 @@ <h2 class="hasAnchor">
     <div id="poppr-0-3" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-0-3" class="anchor"></a>poppr 0.3</h1>
-<div id="new-functions-7" class="section level2">
+<div id="new-functions-8" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-7" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-8" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code>poppr.msn</code> will draw a minimum spanning network for any distance matrix derived from your data set.</li>
 </ul>
 </div>
-<div id="new-features-14" class="section level2">
+<div id="new-features-15" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-14" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-15" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>vignette now has sections describing <code>poppr.msn</code>, <code>diss.dist</code>, <code>greycurve</code>, and a section discussing how to export graphics.</li>
 </ul>
@@ -1184,9 +1229,9 @@ <h2 class="hasAnchor">
     <div id="poppr-0-2-2" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-0-2-2" class="anchor"></a>poppr 0.2.2</h1>
-<div id="new-features-15" class="section level2">
+<div id="new-features-16" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-15" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-16" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>index of association distributions will now feature a rug plot at the bottom as a better way to visualize the distribution of the index of association from the shuffled data sets.</li>
 </ul>
@@ -1195,9 +1240,9 @@ <h2 class="hasAnchor">
     <div id="poppr-0-2-1" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-0-2-1" class="anchor"></a>poppr 0.2.1</h1>
-<div id="new-functions-8" class="section level2">
+<div id="new-functions-9" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-functions-8" class="anchor"></a>NEW FUNCTIONS</h2>
+<a href="#new-functions-9" class="anchor"></a>NEW FUNCTIONS</h2>
 <ul>
 <li>
 <code>diss.dist</code> will produce a distance matrix based on discreet distances.</li>
@@ -1205,9 +1250,9 @@ <h2 class="hasAnchor">
 <code>greycurve</code> will produce a grey scale adjusted to user-supplied parameters. This will be useful for future minimum spanning network functions.</li>
 </ul>
 </div>
-<div id="new-features-16" class="section level2">
+<div id="new-features-17" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-16" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-17" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>
 <code>bruvo.msn</code> can now adjust the edge grey level to be weighted toward either closely or distantly weighted individuals.</li>
@@ -1227,9 +1272,9 @@ <h2 class="hasAnchor">
     <div id="poppr-0-2" class="section level1">
 <h1 class="hasAnchor">
 <a href="#poppr-0-2" class="anchor"></a>poppr 0.2</h1>
-<div id="new-features-17" class="section level2">
+<div id="new-features-18" class="section level2">
 <h2 class="hasAnchor">
-<a href="#new-features-17" class="anchor"></a>NEW FEATURES</h2>
+<a href="#new-features-18" class="anchor"></a>NEW FEATURES</h2>
 <ul>
 <li>Added NEWS file and will now be incrementing version number (3/15/2013)</li>
 </ul>
@@ -1249,6 +1294,8 @@ <h1 class="hasAnchor">
     <div id="tocnav">
       <h2>Contents</h2>
       <ul class="nav nav-pills nav-stacked">
+        <li><a href="#poppr-2-7-1">2.7.1</a></li>
+        <li><a href="#poppr-2-7-0">2.7.0</a></li>
         <li><a href="#poppr-2-6-1">2.6.1</a></li>
         <li><a href="#poppr-2-6-0">2.6.0</a></li>
         <li><a href="#poppr-2-5-0">2.5.0</a></li>
diff --git a/docs/reference/aboot-1.png b/docs/reference/aboot-1.png
index 6e43d9df..4583c9a9 100644
Binary files a/docs/reference/aboot-1.png and b/docs/reference/aboot-1.png differ
diff --git a/docs/reference/aboot-2.png b/docs/reference/aboot-2.png
index 8cac1edf..0ec3718f 100644
Binary files a/docs/reference/aboot-2.png and b/docs/reference/aboot-2.png differ
diff --git a/docs/reference/aboot.html b/docs/reference/aboot.html
index b635413a..aa960c2a 100644
--- a/docs/reference/aboot.html
+++ b/docs/reference/aboot.html
@@ -237,12 +237,12 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='fu'>set.seed</span>(<span class='fl'>9999</span>)
 <span class='co'># Generate a tree using nei's distance</span>
 <span class='no'>neinan</span> <span class='kw'>&lt;-</span> <span class='fu'>aboot</span>(<span class='no'>nan9</span>, <span class='kw'>dist</span> <span class='kw'>=</span> <span class='no'>nei.dist</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Infinite values detected.</span></div><div class='output co'>#&gt; 
Running bootstraps:       100 / 100
-#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='aboot-5.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='aboot-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 <span class='fu'>set.seed</span>(<span class='fl'>9999</span>)
 <span class='co'># Generate a tree using custom distance</span>
 <span class='no'>bindist</span> <span class='kw'>&lt;-</span> <span class='kw'>function</span>(<span class='no'>x</span>) <span class='fu'>dist</span>(<span class='fu'>tab</span>(<span class='no'>x</span>), <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"binary"</span>)
 <span class='no'>binnan</span> <span class='kw'>&lt;-</span> <span class='fu'>aboot</span>(<span class='no'>nan9</span>, <span class='kw'>dist</span> <span class='kw'>=</span> <span class='no'>bindist</span>)</div><div class='output co'>#&gt; 
Running bootstraps:       100 / 100
-#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='aboot-6.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='aboot-2.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 </div><span class='co'># NOT RUN {</span>
 <span class='co'># Distances from other packages.</span>
 <span class='co'>#</span>
diff --git a/docs/reference/bitwise.dist.html b/docs/reference/bitwise.dist.html
index 679c58e8..eb16c5a2 100644
--- a/docs/reference/bitwise.dist.html
+++ b/docs/reference/bitwise.dist.html
@@ -196,7 +196,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt;    @other: a list containing: ancestral.pops 
 #&gt; </div><div class='input'><span class='co'># Assess fraction of different alleles (finer measure, usually the most sensible)</span>
 <span class='fu'>system.time</span>(<span class='no'>xd</span> <span class='kw'>&lt;-</span> <span class='fu'>bitwise.dist</span>(<span class='no'>x</span>))</div><div class='output co'>#&gt;    user  system elapsed 
-#&gt;   0.002   0.000   0.002 </div><div class='input'><span class='no'>xd</span></div><div class='output co'>#&gt;         1      2      3      4      5      6      7      8      9
+#&gt;   0.003   0.001   0.002 </div><div class='input'><span class='no'>xd</span></div><div class='output co'>#&gt;         1      2      3      4      5      6      7      8      9
 #&gt; 2  0.2105                                                        
 #&gt; 3  0.2195 0.2180                                                 
 #&gt; 4  0.3950 0.3825 0.3855                                          
@@ -208,7 +208,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; 10 0.3980 0.3925 0.4005 0.2180 0.2035 0.2220 0.2185 0.2125 0.2140</div><div class='input'>
 <span class='co'># Assess fraction of different loci (coarse measure)</span>
 <span class='fu'>system.time</span>(<span class='no'>xdt</span> <span class='kw'>&lt;-</span> <span class='fu'>bitwise.dist</span>(<span class='no'>x</span>, <span class='kw'>differences_only</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div><div class='output co'>#&gt;    user  system elapsed 
-#&gt;   0.001   0.000   0.002 </div><div class='input'><span class='no'>xdt</span></div><div class='output co'>#&gt;        1     2     3     4     5     6     7     8     9
+#&gt;   0.067   0.001   0.086 </div><div class='input'><span class='no'>xdt</span></div><div class='output co'>#&gt;        1     2     3     4     5     6     7     8     9
 #&gt; 2  0.375                                                
 #&gt; 3  0.394 0.385                                          
 #&gt; 4  0.564 0.546 0.547                                    
diff --git a/docs/reference/boot.ia.html b/docs/reference/boot.ia.html
index 40caa3ff..7358c27b 100644
--- a/docs/reference/boot.ia.html
+++ b/docs/reference/boot.ia.html
@@ -161,7 +161,7 @@ <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See a
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
     <pre class="examples"><div class='input'><span class='fu'>data</span>(<span class='no'>Pinf</span>)
-<span class='fu'>boot.ia</span>(<span class='no'>Pinf</span>, <span class='kw'>reps</span> <span class='kw'>=</span> <span class='fl'>99</span>)</div><div class='output co'>#&gt; 
|==============                                        | 27% ~0 s remaining     
|================================                      | 60% ~0 s remaining     
|=================================================     | 91% ~0 s remaining     </div><div class='output co'>#&gt;           Ia      rbarD
+<span class='fu'>boot.ia</span>(<span class='no'>Pinf</span>, <span class='kw'>reps</span> <span class='kw'>=</span> <span class='fl'>99</span>)</div><div class='output co'>#&gt; 
|=                                                     |  2% ~3 s remaining     
|=================                                     | 32% ~0 s remaining     
|====================================                  | 68% ~0 s remaining     
|===================================================== | 99% ~0 s remaining     </div><div class='output co'>#&gt;           Ia      rbarD
 #&gt; 1  0.6430049 0.07032330
 #&gt; 2  0.5705043 0.06235351
 #&gt; 3  0.5774512 0.06340112
diff --git a/docs/reference/bruvo.boot-1.png b/docs/reference/bruvo.boot-1.png
index 2b1811d2..49c4506f 100644
Binary files a/docs/reference/bruvo.boot-1.png and b/docs/reference/bruvo.boot-1.png differ
diff --git a/docs/reference/bruvo.boot.html b/docs/reference/bruvo.boot.html
index ae492450..4862c683 100644
--- a/docs/reference/bruvo.boot.html
+++ b/docs/reference/bruvo.boot.html
@@ -225,7 +225,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; (note: calculation of node labels can take a while even after the progress bar is full)
 #&gt; 
 #&gt; 
Running bootstraps:       100 / 100
-#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='bruvo.boot-3.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; 
+#&gt; Calculating bootstrap values... done.</div><div class='img'><img src='bruvo.boot-1.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; 
 #&gt; Phylogenetic tree with 10 tips and 9 internal nodes.
 #&gt; 
 #&gt; Tip labels:
diff --git a/docs/reference/bruvo.msn-1.png b/docs/reference/bruvo.msn-1.png
index c9b43205..313c9bc8 100644
Binary files a/docs/reference/bruvo.msn-1.png and b/docs/reference/bruvo.msn-1.png differ
diff --git a/docs/reference/bruvo.msn.html b/docs/reference/bruvo.msn.html
index 935abd36..e10fb7c6 100644
--- a/docs/reference/bruvo.msn.html
+++ b/docs/reference/bruvo.msn.html
@@ -311,11 +311,11 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 
 <span class='co'># View populations 8 and 9 with default colors. </span>
 <span class='fu'>bruvo.msn</span>(<span class='no'>nancycats</span>, <span class='kw'>replen</span> <span class='kw'>=</span> <span class='fu'>rep</span>(<span class='fl'>2</span>, <span class='fl'>9</span>), <span class='kw'>sublist</span><span class='kw'>=</span><span class='fl'>8</span>:<span class='fl'>9</span>, <span class='kw'>vertex.label</span><span class='kw'>=</span><span class='st'>"inds"</span>,
-          <span class='kw'>vertex.label.cex</span><span class='kw'>=</span><span class='fl'>0.7</span>, <span class='kw'>vertex.label.dist</span><span class='kw'>=</span><span class='fl'>0.4</span>)</div><div class='img'><img src='bruvo.msn-3.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; $graph
-#&gt; IGRAPH 7f82159 UNW- 19 18 -- 
+          <span class='kw'>vertex.label.cex</span><span class='kw'>=</span><span class='fl'>0.7</span>, <span class='kw'>vertex.label.dist</span><span class='kw'>=</span><span class='fl'>0.4</span>)</div><div class='img'><img src='bruvo.msn-1.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; $graph
+#&gt; IGRAPH 9d04bb2 UNW- 19 18 -- 
 #&gt; + attr: name (v/c), size (v/n), shape (v/c), pie (v/x), pie.color
 #&gt; | (v/x), label (v/c), weight (e/n), color (e/c), width (e/n)
-#&gt; + edges from 7f82159 (vertex names):
+#&gt; + edges from 9d04bb2 (vertex names):
 #&gt;  [1] N43 --N93  N92 --N112 N94 --N98  N95 --N96  N95 --N97  N98 --N99 
 #&gt;  [7] N98 --N100 N98 --N97  N98 --N111 N100--N108 N93 --N97  N104--N107
 #&gt; [13] N105--N109 N106--N107 N106--N109 N107--N108 N107--N112 N111--N113
diff --git a/docs/reference/coercion-methods.html b/docs/reference/coercion-methods.html
index 307d6bce..83aca1f2 100644
--- a/docs/reference/coercion-methods.html
+++ b/docs/reference/coercion-methods.html
@@ -110,7 +110,9 @@ <h1>Switch between genind and genclone objects.</h1>
 
 <span class='fu'>as.genclone</span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='no'>mlg</span>, <span class='kw'>mlgclass</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
 
-<span class='fu'>genclone2genind</span>(<span class='no'>x</span>)</pre>
+<span class='fu'>genclone2genind</span>(<span class='no'>x</span>)
+
+<span class='fu'>as.genambig</span>(<span class='no'>x</span>)</pre>
     
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
     <table class="ref-arguments">
@@ -142,6 +144,8 @@ <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details
 
     <p>genclone2genind will remove the mlg slot from the genclone object, creating a 
 genind object.</p>
+<p>as.genambig will convert a genind or genclone object to a polysat genambig 
+class.</p>
     
     <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
 
@@ -166,7 +170,9 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt;  // Optional content
 #&gt;    @pop: population of each individual (group size range: 90-97)
 #&gt;    @other: a list containing: population_hierarchy 
-#&gt; </div><div class='input'><span class='no'>Aeut.gc</span> <span class='kw'>&lt;-</span> <span class='fu'>as.genclone</span>(<span class='no'>Aeut</span>)
+#&gt; </div><div class='input'>
+<span class='co'># Conversion to genclone --------------------------------------------------</span>
+<span class='no'>Aeut.gc</span> <span class='kw'>&lt;-</span> <span class='fu'>as.genclone</span>(<span class='no'>Aeut</span>)
 <span class='no'>Aeut.gc</span></div><div class='output co'>#&gt; 
 #&gt; This is a genclone object
 #&gt; -------------------------
@@ -179,7 +185,9 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; Population information:
 #&gt; 
 #&gt;      0 strata. 
-#&gt;      2 populations defined - Athena, Mt. Vernon</div><div class='input'><span class='no'>Aeut.gi</span> <span class='kw'>&lt;-</span> <span class='fu'>genclone2genind</span>(<span class='no'>Aeut.gc</span>)
+#&gt;      2 populations defined - Athena, Mt. Vernon</div><div class='input'>
+<span class='co'># Conversion to genind ----------------------------------------------------</span>
+<span class='no'>Aeut.gi</span> <span class='kw'>&lt;-</span> <span class='fu'>genclone2genind</span>(<span class='no'>Aeut.gc</span>)
 <span class='no'>Aeut.gi</span></div><div class='output co'>#&gt; /// GENIND OBJECT /////////
 #&gt; 
 #&gt;  // 187 individuals; 56 loci; 56 alleles; size: 65.8 Kb
@@ -194,7 +202,22 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt;  // Optional content
 #&gt;    @pop: population of each individual (group size range: 90-97)
 #&gt;    @other: a list containing: population_hierarchy 
-#&gt; </div><div class='input'><span class='fu'>data</span>(<span class='no'>nancycats</span>)
+#&gt; </div><div class='input'>
+<span class='co'># Conversion to polysat's "genambig" class --------------------------------</span>
+<span class='kw'>if</span> (<span class='fu'>require</span>(<span class='st'>"polysat"</span>)) {
+  <span class='fu'>data</span>(<span class='no'>Pinf</span>)
+  <span class='no'>Pinf.gb</span> <span class='kw'>&lt;-</span> <span class='fu'>as.genambig</span>(<span class='no'>Pinf</span>)
+  <span class='fu'>summary</span>(<span class='no'>Pinf.gb</span>)
+}</div><div class='output co'>#&gt; <span class='message'>Loading required package: polysat</span></div><div class='output co'>#&gt; Dataset with allele copy number ambiguity.
+#&gt; Insert dataset description here.
+#&gt; Number of missing genotypes: 10
+#&gt; 86 samples, 11 loci.
+#&gt; 2 populations.
+#&gt; Ploidies: 2 3 NA
+#&gt; Length(s) of microsatellite repeats: NA</div><div class='input'>
+<span class='fu'>data</span>(<span class='no'>nancycats</span>)
+
+<span class='co'># Conversion to bootgen for random sampling of loci -----------------------</span>
 <span class='no'>nan.bg</span>  <span class='kw'>&lt;-</span> <span class='fu'>new</span>(<span class='st'>"bootgen"</span>, <span class='no'>nancycats</span>[<span class='kw'>pop</span> <span class='kw'>=</span> <span class='fl'>9</span>])
 <span class='no'>nan.bg</span></div><div class='output co'>#&gt; An object of class "bootgen"
 #&gt; Slot "type":
@@ -449,7 +472,9 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; 
 #&gt; Slot "call":
 #&gt; NULL
-#&gt; </div><div class='input'><span class='no'>nan.gid</span> <span class='kw'>&lt;-</span> <span class='fu'>bootgen2genind</span>(<span class='no'>nan.bg</span>)
+#&gt; </div><div class='input'>
+<span class='co'># Conversion back to genind -----------------------------------------------</span>
+<span class='no'>nan.gid</span> <span class='kw'>&lt;-</span> <span class='fu'>bootgen2genind</span>(<span class='no'>nan.bg</span>)
 <span class='no'>nan.gid</span></div><div class='output co'>#&gt; /// GENIND OBJECT /////////
 #&gt; 
 #&gt;  // 9 individuals; 9 loci; 108 alleles; size: 23.5 Kb
@@ -464,7 +489,8 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt;    @call: .local(.Object = .Object, tab = ..1)
 #&gt; 
 #&gt;  // Optional content
-#&gt;    - empty -</div></pre>
+#&gt;    - empty -</div><div class='input'>
+</div></pre>
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
     <h2>Contents</h2>
diff --git a/docs/reference/diversity_ci.html b/docs/reference/diversity_ci.html
index 1180384f..c6023c77 100644
--- a/docs/reference/diversity_ci.html
+++ b/docs/reference/diversity_ci.html
@@ -285,7 +285,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='fu'>data</span>(<span class='no'>Pinf</span>)
 <span class='fu'>diversity_ci</span>(<span class='no'>Pinf</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>100L</span>)</div><div class='output co'>#&gt; <span class='message'></span>
 #&gt; <span class='message'>Confidence Intervals have been centered around observed statistic.</span>
-#&gt; <span class='message'>Please see ?diversity_ci for details.</span></div><div class='img'><img src='diversity_ci-3.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; $obs
+#&gt; <span class='message'>Please see ?diversity_ci for details.</span></div><div class='img'><img src='diversity_ci-1.png' alt='' width='700' height='432.632880098887' /></div><div class='output co'>#&gt; $obs
 #&gt;                Index
 #&gt; Pop                    H        G    lambda       E.5
 #&gt;   South America 3.267944 23.29032 0.9570637 0.8825297
diff --git a/docs/reference/filter_stats-1.png b/docs/reference/filter_stats-1.png
index 973419b2..47b7f3ef 100644
Binary files a/docs/reference/filter_stats-1.png and b/docs/reference/filter_stats-1.png differ
diff --git a/docs/reference/filter_stats.html b/docs/reference/filter_stats.html
index ea53a147..72d8ca17 100644
--- a/docs/reference/filter_stats.html
+++ b/docs/reference/filter_stats.html
@@ -201,7 +201,7 @@ <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See a
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
     <pre class="examples"><div class='input'><span class='fu'>data</span>(<span class='no'>Pinf</span>)
 <span class='no'>pinfreps</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='fix_replen.html'>fix_replen</a></span>(<span class='no'>Pinf</span>, <span class='fu'>c</span>(<span class='fl'>2</span>, <span class='fl'>2</span>, <span class='fl'>6</span>, <span class='fl'>2</span>, <span class='fl'>2</span>, <span class='fl'>2</span>, <span class='fl'>2</span>, <span class='fl'>2</span>, <span class='fl'>3</span>, <span class='fl'>3</span>, <span class='fl'>2</span>))
-<span class='fu'>filter_stats</span>(<span class='no'>Pinf</span>, <span class='kw'>distance</span> <span class='kw'>=</span> <span class='no'>bruvo.dist</span>, <span class='kw'>replen</span> <span class='kw'>=</span> <span class='no'>pinfreps</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>threads</span> <span class='kw'>=</span> <span class='fl'>1L</span>)</div><div class='img'><img src='filter_stats-3.png' alt='' width='700' height='432.632880098887' /></div></pre>
+<span class='fu'>filter_stats</span>(<span class='no'>Pinf</span>, <span class='kw'>distance</span> <span class='kw'>=</span> <span class='no'>bruvo.dist</span>, <span class='kw'>replen</span> <span class='kw'>=</span> <span class='no'>pinfreps</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>threads</span> <span class='kw'>=</span> <span class='fl'>1L</span>)</div><div class='img'><img src='filter_stats-1.png' alt='' width='700' height='432.632880098887' /></div></pre>
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
     <h2>Contents</h2>
diff --git a/docs/reference/genotype_curve.html b/docs/reference/genotype_curve.html
index aa53df69..f8a9e49b 100644
--- a/docs/reference/genotype_curve.html
+++ b/docs/reference/genotype_curve.html
@@ -180,7 +180,7 @@ <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
     <pre class="examples"><div class='input'><span class='fu'>data</span>(<span class='no'>nancycats</span>)
-<span class='no'>nan_geno</span> <span class='kw'>&lt;-</span> <span class='fu'>genotype_curve</span>(<span class='no'>nancycats</span>)</div><div class='output co'>#&gt; 
Calculating genotypes for  1/8 loci. Completed iterations:   1%
Calculating genotypes for  1/8 loci. Completed iterations:   2%
Calculating genotypes for  1/8 loci. Completed iterations:   3%
Calculating genotypes for  1/8 loci. Completed iterations:   4%
Calculating genotypes for  1/8 loci. Completed iterations:   5%
Calculating genotypes for  1/8 loci. Completed iterations:   6%
Calculating genotypes for  1/8 loci. Completed iterations:   7%
Calculating genotypes for  1/8 loci. Completed iterations:   8%
Calculating genotypes for  1/8 loci. Completed iterations:   9%
Calculating genotypes for  1/8 loci. Completed iterations:  10%
Calculating genotypes for  1/8 loci. Completed iterations:  11%
Calculating genotypes for  1/8 loci. Completed iterations:  12%
Calculating genotypes for  1/8 loci. Completed iterations:  13%
Calculating genotypes for  1/8 loci. Completed iterations:  14%
Calculating genotypes for  1/8 loci. Completed iterations:  15%
Calculating genotypes for  1/8 loci. Completed iterations:  16%
Calculating genotypes for  1/8 loci. Completed iterations:  17%
Calculating genotypes for  1/8 loci. Completed iterations:  18%
Calculating genotypes for  1/8 loci. Completed iterations:  19%
Calculating genotypes for  1/8 loci. Completed iterations:  20%
Calculating genotypes for  1/8 loci. Completed iterations:  21%
Calculating genotypes for  1/8 loci. Completed iterations:  22%
Calculating genotypes for  1/8 loci. Completed iterations:  23%
Calculating genotypes for  1/8 loci. Completed iterations:  24%
Calculating genotypes for  1/8 loci. Completed iterations:  25%
Calculating genotypes for  1/8 loci. Completed iterations:  26%
Calculating genotypes for  1/8 loci. Completed iterations:  27%
Calculating genotypes for  1/8 loci. Completed iterations:  28%
Calculating genotypes for  1/8 loci. Completed iterations:  29%
Calculating genotypes for  1/8 loci. Completed iterations:  30%
Calculating genotypes for  1/8 loci. Completed iterations:  31%
Calculating genotypes for  1/8 loci. Completed iterations:  32%
Calculating genotypes for  1/8 loci. Completed iterations:  33%
Calculating genotypes for  1/8 loci. Completed iterations:  34%
Calculating genotypes for  1/8 loci. Completed iterations:  35%
Calculating genotypes for  1/8 loci. Completed iterations:  36%
Calculating genotypes for  1/8 loci. Completed iterations:  37%
Calculating genotypes for  1/8 loci. Completed iterations:  38%
Calculating genotypes for  1/8 loci. Completed iterations:  39%
Calculating genotypes for  1/8 loci. Completed iterations:  40%
Calculating genotypes for  1/8 loci. Completed iterations:  41%
Calculating genotypes for  1/8 loci. Completed iterations:  42%
Calculating genotypes for  1/8 loci. Completed iterations:  43%
Calculating genotypes for  1/8 loci. Completed iterations:  44%
Calculating genotypes for  1/8 loci. Completed iterations:  45%
Calculating genotypes for  1/8 loci. Completed iterations:  46%
Calculating genotypes for  1/8 loci. Completed iterations:  47%
Calculating genotypes for  1/8 loci. Completed iterations:  48%
Calculating genotypes for  1/8 loci. Completed iterations:  49%
Calculating genotypes for  1/8 loci. Completed iterations:  50%
Calculating genotypes for  1/8 loci. Completed iterations:  51%
Calculating genotypes for  1/8 loci. Completed iterations:  52%
Calculating genotypes for  1/8 loci. Completed iterations:  53%
Calculating genotypes for  1/8 loci. Completed iterations:  54%
Calculating genotypes for  1/8 loci. Completed iterations:  55%
Calculating genotypes for  1/8 loci. Completed iterations:  56%
Calculating genotypes for  1/8 loci. Completed iterations:  57%
Calculating genotypes for  1/8 loci. Completed iterations:  58%
Calculating genotypes for  1/8 loci. Completed iterations:  59%
Calculating genotypes for  1/8 loci. Completed iterations:  60%
Calculating genotypes for  1/8 loci. Completed iterations:  61%
Calculating genotypes for  1/8 loci. Completed iterations:  62%
Calculating genotypes for  1/8 loci. Completed iterations:  63%
Calculating genotypes for  1/8 loci. Completed iterations:  64%
Calculating genotypes for  1/8 loci. Completed iterations:  65%
Calculating genotypes for  1/8 loci. Completed iterations:  66%
Calculating genotypes for  1/8 loci. Completed iterations:  67%
Calculating genotypes for  1/8 loci. Completed iterations:  68%
Calculating genotypes for  1/8 loci. Completed iterations:  69%
Calculating genotypes for  1/8 loci. Completed iterations:  70%
Calculating genotypes for  1/8 loci. Completed iterations:  71%
Calculating genotypes for  1/8 loci. Completed iterations:  72%
Calculating genotypes for  1/8 loci. Completed iterations:  73%
Calculating genotypes for  1/8 loci. Completed iterations:  74%
Calculating genotypes for  1/8 loci. Completed iterations:  75%
Calculating genotypes for  1/8 loci. Completed iterations:  76%
Calculating genotypes for  1/8 loci. Completed iterations:  77%
Calculating genotypes for  1/8 loci. Completed iterations:  78%
Calculating genotypes for  1/8 loci. Completed iterations:  79%
Calculating genotypes for  1/8 loci. Completed iterations:  80%
Calculating genotypes for  1/8 loci. Completed iterations:  81%
Calculating genotypes for  1/8 loci. Completed iterations:  82%
Calculating genotypes for  1/8 loci. Completed iterations:  83%
Calculating genotypes for  1/8 loci. Completed iterations:  84%
Calculating genotypes for  1/8 loci. Completed iterations:  85%
Calculating genotypes for  1/8 loci. Completed iterations:  86%
Calculating genotypes for  1/8 loci. Completed iterations:  87%
Calculating genotypes for  1/8 loci. Completed iterations:  88%
Calculating genotypes for  1/8 loci. Completed iterations:  89%
Calculating genotypes for  1/8 loci. Completed iterations:  90%
Calculating genotypes for  1/8 loci. Completed iterations:  91%
Calculating genotypes for  1/8 loci. Completed iterations:  92%
Calculating genotypes for  1/8 loci. Completed iterations:  93%
Calculating genotypes for  1/8 loci. Completed iterations:  94%
Calculating genotypes for  1/8 loci. Completed iterations:  95%
Calculating genotypes for  1/8 loci. Completed iterations:  96%
Calculating genotypes for  1/8 loci. Completed iterations:  97%
Calculating genotypes for  1/8 loci. Completed iterations:  98%
Calculating genotypes for  1/8 loci. Completed iterations:  99%
Calculating genotypes for  1/8 loci. Completed iterations: 100%
Calculating genotypes for  2/8 loci. Completed iterations:   1%
Calculating genotypes for  2/8 loci. Completed iterations:   2%
Calculating genotypes for  2/8 loci. Completed iterations:   3%
Calculating genotypes for  2/8 loci. Completed iterations:   4%
Calculating genotypes for  2/8 loci. Completed iterations:   5%
Calculating genotypes for  2/8 loci. Completed iterations:   6%
Calculating genotypes for  2/8 loci. Completed iterations:   7%
Calculating genotypes for  2/8 loci. Completed iterations:   8%
Calculating genotypes for  2/8 loci. Completed iterations:   9%
Calculating genotypes for  2/8 loci. Completed iterations:  10%
Calculating genotypes for  2/8 loci. Completed iterations:  11%
Calculating genotypes for  2/8 loci. Completed iterations:  12%
Calculating genotypes for  2/8 loci. Completed iterations:  13%
Calculating genotypes for  2/8 loci. Completed iterations:  14%
Calculating genotypes for  2/8 loci. Completed iterations:  15%
Calculating genotypes for  2/8 loci. Completed iterations:  16%
Calculating genotypes for  2/8 loci. Completed iterations:  17%
Calculating genotypes for  2/8 loci. Completed iterations:  18%
Calculating genotypes for  2/8 loci. Completed iterations:  19%
Calculating genotypes for  2/8 loci. Completed iterations:  20%
Calculating genotypes for  2/8 loci. Completed iterations:  21%
Calculating genotypes for  2/8 loci. Completed iterations:  22%
Calculating genotypes for  2/8 loci. Completed iterations:  23%
Calculating genotypes for  2/8 loci. Completed iterations:  24%
Calculating genotypes for  2/8 loci. Completed iterations:  25%
Calculating genotypes for  2/8 loci. Completed iterations:  26%
Calculating genotypes for  2/8 loci. Completed iterations:  27%
Calculating genotypes for  2/8 loci. Completed iterations:  28%
Calculating genotypes for  2/8 loci. Completed iterations:  29%
Calculating genotypes for  2/8 loci. Completed iterations:  30%
Calculating genotypes for  2/8 loci. Completed iterations:  31%
Calculating genotypes for  2/8 loci. Completed iterations:  32%
Calculating genotypes for  2/8 loci. Completed iterations:  33%
Calculating genotypes for  2/8 loci. Completed iterations:  34%
Calculating genotypes for  2/8 loci. Completed iterations:  35%
Calculating genotypes for  2/8 loci. Completed iterations:  36%
Calculating genotypes for  2/8 loci. Completed iterations:  37%
Calculating genotypes for  2/8 loci. Completed iterations:  38%
Calculating genotypes for  2/8 loci. Completed iterations:  39%
Calculating genotypes for  2/8 loci. Completed iterations:  40%
Calculating genotypes for  2/8 loci. Completed iterations:  41%
Calculating genotypes for  2/8 loci. Completed iterations:  42%
Calculating genotypes for  2/8 loci. Completed iterations:  43%
Calculating genotypes for  2/8 loci. Completed iterations:  44%
Calculating genotypes for  2/8 loci. Completed iterations:  45%
Calculating genotypes for  2/8 loci. Completed iterations:  46%
Calculating genotypes for  2/8 loci. Completed iterations:  47%
Calculating genotypes for  2/8 loci. Completed iterations:  48%
Calculating genotypes for  2/8 loci. Completed iterations:  49%
Calculating genotypes for  2/8 loci. Completed iterations:  50%
Calculating genotypes for  2/8 loci. Completed iterations:  51%
Calculating genotypes for  2/8 loci. Completed iterations:  52%
Calculating genotypes for  2/8 loci. Completed iterations:  53%
Calculating genotypes for  2/8 loci. Completed iterations:  54%
Calculating genotypes for  2/8 loci. Completed iterations:  55%
Calculating genotypes for  2/8 loci. Completed iterations:  56%
Calculating genotypes for  2/8 loci. Completed iterations:  57%
Calculating genotypes for  2/8 loci. Completed iterations:  58%
Calculating genotypes for  2/8 loci. Completed iterations:  59%
Calculating genotypes for  2/8 loci. Completed iterations:  60%
Calculating genotypes for  2/8 loci. Completed iterations:  61%
Calculating genotypes for  2/8 loci. Completed iterations:  62%
Calculating genotypes for  2/8 loci. Completed iterations:  63%
Calculating genotypes for  2/8 loci. Completed iterations:  64%
Calculating genotypes for  2/8 loci. Completed iterations:  65%
Calculating genotypes for  2/8 loci. Completed iterations:  66%
Calculating genotypes for  2/8 loci. Completed iterations:  67%
Calculating genotypes for  2/8 loci. Completed iterations:  68%
Calculating genotypes for  2/8 loci. Completed iterations:  69%
Calculating genotypes for  2/8 loci. Completed iterations:  70%
Calculating genotypes for  2/8 loci. Completed iterations:  71%
Calculating genotypes for  2/8 loci. Completed iterations:  72%
Calculating genotypes for  2/8 loci. Completed iterations:  73%
Calculating genotypes for  2/8 loci. Completed iterations:  74%
Calculating genotypes for  2/8 loci. Completed iterations:  75%
Calculating genotypes for  2/8 loci. Completed iterations:  76%
Calculating genotypes for  2/8 loci. Completed iterations:  77%
Calculating genotypes for  2/8 loci. Completed iterations:  78%
Calculating genotypes for  2/8 loci. Completed iterations:  79%
Calculating genotypes for  2/8 loci. Completed iterations:  80%
Calculating genotypes for  2/8 loci. Completed iterations:  81%
Calculating genotypes for  2/8 loci. Completed iterations:  82%
Calculating genotypes for  2/8 loci. Completed iterations:  83%
Calculating genotypes for  2/8 loci. Completed iterations:  84%
Calculating genotypes for  2/8 loci. Completed iterations:  85%
Calculating genotypes for  2/8 loci. Completed iterations:  86%
Calculating genotypes for  2/8 loci. Completed iterations:  87%
Calculating genotypes for  2/8 loci. Completed iterations:  88%
Calculating genotypes for  2/8 loci. Completed iterations:  89%
Calculating genotypes for  2/8 loci. Completed iterations:  90%
Calculating genotypes for  2/8 loci. Completed iterations:  91%
Calculating genotypes for  2/8 loci. Completed iterations:  92%
Calculating genotypes for  2/8 loci. Completed iterations:  93%
Calculating genotypes for  2/8 loci. Completed iterations:  94%
Calculating genotypes for  2/8 loci. Completed iterations:  95%
Calculating genotypes for  2/8 loci. Completed iterations:  96%
Calculating genotypes for  2/8 loci. Completed iterations:  97%
Calculating genotypes for  2/8 loci. Completed iterations:  98%
Calculating genotypes for  2/8 loci. Completed iterations:  99%
Calculating genotypes for  2/8 loci. Completed iterations: 100%
Calculating genotypes for  3/8 loci. Completed iterations:   1%
Calculating genotypes for  3/8 loci. Completed iterations:   2%
Calculating genotypes for  3/8 loci. Completed iterations:   3%
Calculating genotypes for  3/8 loci. Completed iterations:   4%
Calculating genotypes for  3/8 loci. Completed iterations:   5%
Calculating genotypes for  3/8 loci. Completed iterations:   6%
Calculating genotypes for  3/8 loci. Completed iterations:   7%
Calculating genotypes for  3/8 loci. Completed iterations:   8%
Calculating genotypes for  3/8 loci. Completed iterations:   9%
Calculating genotypes for  3/8 loci. Completed iterations:  10%
Calculating genotypes for  3/8 loci. Completed iterations:  11%
Calculating genotypes for  3/8 loci. Completed iterations:  12%
Calculating genotypes for  3/8 loci. Completed iterations:  13%
Calculating genotypes for  3/8 loci. Completed iterations:  14%
Calculating genotypes for  3/8 loci. Completed iterations:  15%
Calculating genotypes for  3/8 loci. Completed iterations:  16%
Calculating genotypes for  3/8 loci. Completed iterations:  17%
Calculating genotypes for  3/8 loci. Completed iterations:  18%
Calculating genotypes for  3/8 loci. Completed iterations:  19%
Calculating genotypes for  3/8 loci. Completed iterations:  20%
Calculating genotypes for  3/8 loci. Completed iterations:  21%
Calculating genotypes for  3/8 loci. Completed iterations:  22%
Calculating genotypes for  3/8 loci. Completed iterations:  23%
Calculating genotypes for  3/8 loci. Completed iterations:  24%
Calculating genotypes for  3/8 loci. Completed iterations:  25%
Calculating genotypes for  3/8 loci. Completed iterations:  26%
Calculating genotypes for  3/8 loci. Completed iterations:  27%
Calculating genotypes for  3/8 loci. Completed iterations:  28%
Calculating genotypes for  3/8 loci. Completed iterations:  29%
Calculating genotypes for  3/8 loci. Completed iterations:  30%
Calculating genotypes for  3/8 loci. Completed iterations:  31%
Calculating genotypes for  3/8 loci. Completed iterations:  32%
Calculating genotypes for  3/8 loci. Completed iterations:  33%
Calculating genotypes for  3/8 loci. Completed iterations:  34%
Calculating genotypes for  3/8 loci. Completed iterations:  35%
Calculating genotypes for  3/8 loci. Completed iterations:  36%
Calculating genotypes for  3/8 loci. Completed iterations:  37%
Calculating genotypes for  3/8 loci. Completed iterations:  38%
Calculating genotypes for  3/8 loci. Completed iterations:  39%
Calculating genotypes for  3/8 loci. Completed iterations:  40%
Calculating genotypes for  3/8 loci. Completed iterations:  41%
Calculating genotypes for  3/8 loci. Completed iterations:  42%
Calculating genotypes for  3/8 loci. Completed iterations:  43%
Calculating genotypes for  3/8 loci. Completed iterations:  44%
Calculating genotypes for  3/8 loci. Completed iterations:  45%
Calculating genotypes for  3/8 loci. Completed iterations:  46%
Calculating genotypes for  3/8 loci. Completed iterations:  47%
Calculating genotypes for  3/8 loci. Completed iterations:  48%
Calculating genotypes for  3/8 loci. Completed iterations:  49%
Calculating genotypes for  3/8 loci. Completed iterations:  50%
Calculating genotypes for  3/8 loci. Completed iterations:  51%
Calculating genotypes for  3/8 loci. Completed iterations:  52%
Calculating genotypes for  3/8 loci. Completed iterations:  53%
Calculating genotypes for  3/8 loci. Completed iterations:  54%
Calculating genotypes for  3/8 loci. Completed iterations:  55%
Calculating genotypes for  3/8 loci. Completed iterations:  56%
Calculating genotypes for  3/8 loci. Completed iterations:  57%
Calculating genotypes for  3/8 loci. Completed iterations:  58%
Calculating genotypes for  3/8 loci. Completed iterations:  59%
Calculating genotypes for  3/8 loci. Completed iterations:  60%
Calculating genotypes for  3/8 loci. Completed iterations:  61%
Calculating genotypes for  3/8 loci. Completed iterations:  62%
Calculating genotypes for  3/8 loci. Completed iterations:  63%
Calculating genotypes for  3/8 loci. Completed iterations:  64%
Calculating genotypes for  3/8 loci. Completed iterations:  65%
Calculating genotypes for  3/8 loci. Completed iterations:  66%
Calculating genotypes for  3/8 loci. Completed iterations:  67%
Calculating genotypes for  3/8 loci. Completed iterations:  68%
Calculating genotypes for  3/8 loci. Completed iterations:  69%
Calculating genotypes for  3/8 loci. Completed iterations:  70%
Calculating genotypes for  3/8 loci. Completed iterations:  71%
Calculating genotypes for  3/8 loci. Completed iterations:  72%
Calculating genotypes for  3/8 loci. Completed iterations:  73%
Calculating genotypes for  3/8 loci. Completed iterations:  74%
Calculating genotypes for  3/8 loci. Completed iterations:  75%
Calculating genotypes for  3/8 loci. Completed iterations:  76%
Calculating genotypes for  3/8 loci. Completed iterations:  77%
Calculating genotypes for  3/8 loci. Completed iterations:  78%
Calculating genotypes for  3/8 loci. Completed iterations:  79%
Calculating genotypes for  3/8 loci. Completed iterations:  80%
Calculating genotypes for  3/8 loci. Completed iterations:  81%
Calculating genotypes for  3/8 loci. Completed iterations:  82%
Calculating genotypes for  3/8 loci. Completed iterations:  83%
Calculating genotypes for  3/8 loci. Completed iterations:  84%
Calculating genotypes for  3/8 loci. Completed iterations:  85%
Calculating genotypes for  3/8 loci. Completed iterations:  86%
Calculating genotypes for  3/8 loci. Completed iterations:  87%
Calculating genotypes for  3/8 loci. Completed iterations:  88%
Calculating genotypes for  3/8 loci. Completed iterations:  89%
Calculating genotypes for  3/8 loci. Completed iterations:  90%
Calculating genotypes for  3/8 loci. Completed iterations:  91%
Calculating genotypes for  3/8 loci. Completed iterations:  92%
Calculating genotypes for  3/8 loci. Completed iterations:  93%
Calculating genotypes for  3/8 loci. Completed iterations:  94%
Calculating genotypes for  3/8 loci. Completed iterations:  95%
Calculating genotypes for  3/8 loci. Completed iterations:  96%
Calculating genotypes for  3/8 loci. Completed iterations:  97%
Calculating genotypes for  3/8 loci. Completed iterations:  98%
Calculating genotypes for  3/8 loci. Completed iterations:  99%
Calculating genotypes for  3/8 loci. Completed iterations: 100%
Calculating genotypes for  4/8 loci. Completed iterations:   1%
Calculating genotypes for  4/8 loci. Completed iterations:   2%
Calculating genotypes for  4/8 loci. Completed iterations:   3%
Calculating genotypes for  4/8 loci. Completed iterations:   4%
Calculating genotypes for  4/8 loci. Completed iterations:   5%
Calculating genotypes for  4/8 loci. Completed iterations:   6%
Calculating genotypes for  4/8 loci. Completed iterations:   7%
Calculating genotypes for  4/8 loci. Completed iterations:   8%
Calculating genotypes for  4/8 loci. Completed iterations:   9%
Calculating genotypes for  4/8 loci. Completed iterations:  10%
Calculating genotypes for  4/8 loci. Completed iterations:  11%
Calculating genotypes for  4/8 loci. Completed iterations:  12%
Calculating genotypes for  4/8 loci. Completed iterations:  13%
Calculating genotypes for  4/8 loci. Completed iterations:  14%
Calculating genotypes for  4/8 loci. Completed iterations:  15%
Calculating genotypes for  4/8 loci. Completed iterations:  16%
Calculating genotypes for  4/8 loci. Completed iterations:  17%
Calculating genotypes for  4/8 loci. Completed iterations:  18%
Calculating genotypes for  4/8 loci. Completed iterations:  19%
Calculating genotypes for  4/8 loci. Completed iterations:  20%
Calculating genotypes for  4/8 loci. Completed iterations:  21%
Calculating genotypes for  4/8 loci. Completed iterations:  22%
Calculating genotypes for  4/8 loci. Completed iterations:  23%
Calculating genotypes for  4/8 loci. Completed iterations:  24%
Calculating genotypes for  4/8 loci. Completed iterations:  25%
Calculating genotypes for  4/8 loci. Completed iterations:  26%
Calculating genotypes for  4/8 loci. Completed iterations:  27%
Calculating genotypes for  4/8 loci. Completed iterations:  28%
Calculating genotypes for  4/8 loci. Completed iterations:  29%
Calculating genotypes for  4/8 loci. Completed iterations:  30%
Calculating genotypes for  4/8 loci. Completed iterations:  31%
Calculating genotypes for  4/8 loci. Completed iterations:  32%
Calculating genotypes for  4/8 loci. Completed iterations:  33%
Calculating genotypes for  4/8 loci. Completed iterations:  34%
Calculating genotypes for  4/8 loci. Completed iterations:  35%
Calculating genotypes for  4/8 loci. Completed iterations:  36%
Calculating genotypes for  4/8 loci. Completed iterations:  37%
Calculating genotypes for  4/8 loci. Completed iterations:  38%
Calculating genotypes for  4/8 loci. Completed iterations:  39%
Calculating genotypes for  4/8 loci. Completed iterations:  40%
Calculating genotypes for  4/8 loci. Completed iterations:  41%
Calculating genotypes for  4/8 loci. Completed iterations:  42%
Calculating genotypes for  4/8 loci. Completed iterations:  43%
Calculating genotypes for  4/8 loci. Completed iterations:  44%
Calculating genotypes for  4/8 loci. Completed iterations:  45%
Calculating genotypes for  4/8 loci. Completed iterations:  46%
Calculating genotypes for  4/8 loci. Completed iterations:  47%
Calculating genotypes for  4/8 loci. Completed iterations:  48%
Calculating genotypes for  4/8 loci. Completed iterations:  49%
Calculating genotypes for  4/8 loci. Completed iterations:  50%
Calculating genotypes for  4/8 loci. Completed iterations:  51%
Calculating genotypes for  4/8 loci. Completed iterations:  52%
Calculating genotypes for  4/8 loci. Completed iterations:  53%
Calculating genotypes for  4/8 loci. Completed iterations:  54%
Calculating genotypes for  4/8 loci. Completed iterations:  55%
Calculating genotypes for  4/8 loci. Completed iterations:  56%
Calculating genotypes for  4/8 loci. Completed iterations:  57%
Calculating genotypes for  4/8 loci. Completed iterations:  58%
Calculating genotypes for  4/8 loci. Completed iterations:  59%
Calculating genotypes for  4/8 loci. Completed iterations:  60%
Calculating genotypes for  4/8 loci. Completed iterations:  61%
Calculating genotypes for  4/8 loci. Completed iterations:  62%
Calculating genotypes for  4/8 loci. Completed iterations:  63%
Calculating genotypes for  4/8 loci. Completed iterations:  64%
Calculating genotypes for  4/8 loci. Completed iterations:  65%
Calculating genotypes for  4/8 loci. Completed iterations:  66%
Calculating genotypes for  4/8 loci. Completed iterations:  67%
Calculating genotypes for  4/8 loci. Completed iterations:  68%
Calculating genotypes for  4/8 loci. Completed iterations:  69%
Calculating genotypes for  4/8 loci. Completed iterations:  70%
Calculating genotypes for  4/8 loci. Completed iterations:  71%
Calculating genotypes for  4/8 loci. Completed iterations:  72%
Calculating genotypes for  4/8 loci. Completed iterations:  73%
Calculating genotypes for  4/8 loci. Completed iterations:  74%
Calculating genotypes for  4/8 loci. Completed iterations:  75%
Calculating genotypes for  4/8 loci. Completed iterations:  76%
Calculating genotypes for  4/8 loci. Completed iterations:  77%
Calculating genotypes for  4/8 loci. Completed iterations:  78%
Calculating genotypes for  4/8 loci. Completed iterations:  79%
Calculating genotypes for  4/8 loci. Completed iterations:  80%
Calculating genotypes for  4/8 loci. Completed iterations:  81%
Calculating genotypes for  4/8 loci. Completed iterations:  82%
Calculating genotypes for  4/8 loci. Completed iterations:  83%
Calculating genotypes for  4/8 loci. Completed iterations:  84%
Calculating genotypes for  4/8 loci. Completed iterations:  85%
Calculating genotypes for  4/8 loci. Completed iterations:  86%
Calculating genotypes for  4/8 loci. Completed iterations:  87%
Calculating genotypes for  4/8 loci. Completed iterations:  88%
Calculating genotypes for  4/8 loci. Completed iterations:  89%
Calculating genotypes for  4/8 loci. Completed iterations:  90%
Calculating genotypes for  4/8 loci. Completed iterations:  91%
Calculating genotypes for  4/8 loci. Completed iterations:  92%
Calculating genotypes for  4/8 loci. Completed iterations:  93%
Calculating genotypes for  4/8 loci. Completed iterations:  94%
Calculating genotypes for  4/8 loci. Completed iterations:  95%
Calculating genotypes for  4/8 loci. Completed iterations:  96%
Calculating genotypes for  4/8 loci. Completed iterations:  97%
Calculating genotypes for  4/8 loci. Completed iterations:  98%
Calculating genotypes for  4/8 loci. Completed iterations:  99%
Calculating genotypes for  4/8 loci. Completed iterations: 100%
Calculating genotypes for  5/8 loci. Completed iterations:   1%
Calculating genotypes for  5/8 loci. Completed iterations:   2%
Calculating genotypes for  5/8 loci. Completed iterations:   3%
Calculating genotypes for  5/8 loci. Completed iterations:   4%
Calculating genotypes for  5/8 loci. Completed iterations:   5%
Calculating genotypes for  5/8 loci. Completed iterations:   6%
Calculating genotypes for  5/8 loci. Completed iterations:   7%
Calculating genotypes for  5/8 loci. Completed iterations:   8%
Calculating genotypes for  5/8 loci. Completed iterations:   9%
Calculating genotypes for  5/8 loci. Completed iterations:  10%
Calculating genotypes for  5/8 loci. Completed iterations:  11%
Calculating genotypes for  5/8 loci. Completed iterations:  12%
Calculating genotypes for  5/8 loci. Completed iterations:  13%
Calculating genotypes for  5/8 loci. Completed iterations:  14%
Calculating genotypes for  5/8 loci. Completed iterations:  15%
Calculating genotypes for  5/8 loci. Completed iterations:  16%
Calculating genotypes for  5/8 loci. Completed iterations:  17%
Calculating genotypes for  5/8 loci. Completed iterations:  18%
Calculating genotypes for  5/8 loci. Completed iterations:  19%
Calculating genotypes for  5/8 loci. Completed iterations:  20%
Calculating genotypes for  5/8 loci. Completed iterations:  21%
Calculating genotypes for  5/8 loci. Completed iterations:  22%
Calculating genotypes for  5/8 loci. Completed iterations:  23%
Calculating genotypes for  5/8 loci. Completed iterations:  24%
Calculating genotypes for  5/8 loci. Completed iterations:  25%
Calculating genotypes for  5/8 loci. Completed iterations:  26%
Calculating genotypes for  5/8 loci. Completed iterations:  27%
Calculating genotypes for  5/8 loci. Completed iterations:  28%
Calculating genotypes for  5/8 loci. Completed iterations:  29%
Calculating genotypes for  5/8 loci. Completed iterations:  30%
Calculating genotypes for  5/8 loci. Completed iterations:  31%
Calculating genotypes for  5/8 loci. Completed iterations:  32%
Calculating genotypes for  5/8 loci. Completed iterations:  33%
Calculating genotypes for  5/8 loci. Completed iterations:  34%
Calculating genotypes for  5/8 loci. Completed iterations:  35%
Calculating genotypes for  5/8 loci. Completed iterations:  36%
Calculating genotypes for  5/8 loci. Completed iterations:  37%
Calculating genotypes for  5/8 loci. Completed iterations:  38%
Calculating genotypes for  5/8 loci. Completed iterations:  39%
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Calculating genotypes for  5/8 loci. Completed iterations:  47%
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Calculating genotypes for  5/8 loci. Completed iterations:  50%
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Calculating genotypes for  5/8 loci. Completed iterations:  52%
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Calculating genotypes for  5/8 loci. Completed iterations:  54%
Calculating genotypes for  5/8 loci. Completed iterations:  55%
Calculating genotypes for  5/8 loci. Completed iterations:  56%
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Calculating genotypes for  5/8 loci. Completed iterations:  58%
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Calculating genotypes for  5/8 loci. Completed iterations:  61%
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Calculating genotypes for  5/8 loci. Completed iterations:  68%
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Calculating genotypes for  5/8 loci. Completed iterations:  71%
Calculating genotypes for  5/8 loci. Completed iterations:  72%
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Calculating genotypes for  5/8 loci. Completed iterations:  74%
Calculating genotypes for  5/8 loci. Completed iterations:  75%
Calculating genotypes for  5/8 loci. Completed iterations:  76%
Calculating genotypes for  5/8 loci. Completed iterations:  77%
Calculating genotypes for  5/8 loci. Completed iterations:  78%
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Calculating genotypes for  5/8 loci. Completed iterations:  80%
Calculating genotypes for  5/8 loci. Completed iterations:  81%
Calculating genotypes for  5/8 loci. Completed iterations:  82%
Calculating genotypes for  5/8 loci. Completed iterations:  83%
Calculating genotypes for  5/8 loci. Completed iterations:  84%
Calculating genotypes for  5/8 loci. Completed iterations:  85%
Calculating genotypes for  5/8 loci. Completed iterations:  86%
Calculating genotypes for  5/8 loci. Completed iterations:  87%
Calculating genotypes for  5/8 loci. Completed iterations:  88%
Calculating genotypes for  5/8 loci. Completed iterations:  89%
Calculating genotypes for  5/8 loci. Completed iterations:  90%
Calculating genotypes for  5/8 loci. Completed iterations:  91%
Calculating genotypes for  5/8 loci. Completed iterations:  92%
Calculating genotypes for  5/8 loci. Completed iterations:  93%
Calculating genotypes for  5/8 loci. Completed iterations:  94%
Calculating genotypes for  5/8 loci. Completed iterations:  95%
Calculating genotypes for  5/8 loci. Completed iterations:  96%
Calculating genotypes for  5/8 loci. Completed iterations:  97%
Calculating genotypes for  5/8 loci. Completed iterations:  98%
Calculating genotypes for  5/8 loci. Completed iterations:  99%
Calculating genotypes for  5/8 loci. Completed iterations: 100%
Calculating genotypes for  6/8 loci. Completed iterations:   1%
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Calculating genotypes for  6/8 loci. Completed iterations:   3%
Calculating genotypes for  6/8 loci. Completed iterations:   4%
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Calculating genotypes for  6/8 loci. Completed iterations:   9%
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Calculating genotypes for  6/8 loci. Completed iterations:  48%
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Calculating genotypes for  6/8 loci. Completed iterations:  67%
Calculating genotypes for  6/8 loci. Completed iterations:  68%
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Calculating genotypes for  6/8 loci. Completed iterations:  71%
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Calculating genotypes for  6/8 loci. Completed iterations:  86%
Calculating genotypes for  6/8 loci. Completed iterations:  87%
Calculating genotypes for  6/8 loci. Completed iterations:  88%
Calculating genotypes for  6/8 loci. Completed iterations:  89%
Calculating genotypes for  6/8 loci. Completed iterations:  90%
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Calculating genotypes for  6/8 loci. Completed iterations:  96%
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Calculating genotypes for  6/8 loci. Completed iterations: 100%
Calculating genotypes for  7/8 loci. Completed iterations:   1%
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Calculating genotypes for  8/8 loci. Completed iterations:   1%
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Calculating genotypes for  8/8 loci. Completed iterations:  37%
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Calculating genotypes for  8/8 loci. Completed iterations:  40%
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Calculating genotypes for  8/8 loci. Completed iterations:  42%
Calculating genotypes for  8/8 loci. Completed iterations:  43%
Calculating genotypes for  8/8 loci. Completed iterations:  44%
Calculating genotypes for  8/8 loci. Completed iterations:  45%
Calculating genotypes for  8/8 loci. Completed iterations:  46%
Calculating genotypes for  8/8 loci. Completed iterations:  47%
Calculating genotypes for  8/8 loci. Completed iterations:  48%
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Calculating genotypes for  8/8 loci. Completed iterations:  50%
Calculating genotypes for  8/8 loci. Completed iterations:  51%
Calculating genotypes for  8/8 loci. Completed iterations:  52%
Calculating genotypes for  8/8 loci. Completed iterations:  53%
Calculating genotypes for  8/8 loci. Completed iterations:  54%
Calculating genotypes for  8/8 loci. Completed iterations:  55%
Calculating genotypes for  8/8 loci. Completed iterations:  56%
Calculating genotypes for  8/8 loci. Completed iterations:  57%
Calculating genotypes for  8/8 loci. Completed iterations:  58%
Calculating genotypes for  8/8 loci. Completed iterations:  59%
Calculating genotypes for  8/8 loci. Completed iterations:  60%
Calculating genotypes for  8/8 loci. Completed iterations:  61%
Calculating genotypes for  8/8 loci. Completed iterations:  62%
Calculating genotypes for  8/8 loci. Completed iterations:  63%
Calculating genotypes for  8/8 loci. Completed iterations:  64%
Calculating genotypes for  8/8 loci. Completed iterations:  65%
Calculating genotypes for  8/8 loci. Completed iterations:  66%
Calculating genotypes for  8/8 loci. Completed iterations:  67%
Calculating genotypes for  8/8 loci. Completed iterations:  68%
Calculating genotypes for  8/8 loci. Completed iterations:  69%
Calculating genotypes for  8/8 loci. Completed iterations:  70%
Calculating genotypes for  8/8 loci. Completed iterations:  71%
Calculating genotypes for  8/8 loci. Completed iterations:  72%
Calculating genotypes for  8/8 loci. Completed iterations:  73%
Calculating genotypes for  8/8 loci. Completed iterations:  74%
Calculating genotypes for  8/8 loci. Completed iterations:  75%
Calculating genotypes for  8/8 loci. Completed iterations:  76%
Calculating genotypes for  8/8 loci. Completed iterations:  77%
Calculating genotypes for  8/8 loci. Completed iterations:  78%
Calculating genotypes for  8/8 loci. Completed iterations:  79%
Calculating genotypes for  8/8 loci. Completed iterations:  80%
Calculating genotypes for  8/8 loci. Completed iterations:  81%
Calculating genotypes for  8/8 loci. Completed iterations:  82%
Calculating genotypes for  8/8 loci. Completed iterations:  83%
Calculating genotypes for  8/8 loci. Completed iterations:  84%
Calculating genotypes for  8/8 loci. Completed iterations:  85%
Calculating genotypes for  8/8 loci. Completed iterations:  86%
Calculating genotypes for  8/8 loci. Completed iterations:  87%
Calculating genotypes for  8/8 loci. Completed iterations:  88%
Calculating genotypes for  8/8 loci. Completed iterations:  89%
Calculating genotypes for  8/8 loci. Completed iterations:  90%
Calculating genotypes for  8/8 loci. Completed iterations:  91%
Calculating genotypes for  8/8 loci. Completed iterations:  92%
Calculating genotypes for  8/8 loci. Completed iterations:  93%
Calculating genotypes for  8/8 loci. Completed iterations:  94%
Calculating genotypes for  8/8 loci. Completed iterations:  95%
Calculating genotypes for  8/8 loci. Completed iterations:  96%
Calculating genotypes for  8/8 loci. Completed iterations:  97%
Calculating genotypes for  8/8 loci. Completed iterations:  98%
Calculating genotypes for  8/8 loci. Completed iterations:  99%
Calculating genotypes for  8/8 loci. Completed iterations: 100%</div><div class='img'><img src='genotype_curve-3.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
+<span class='no'>nan_geno</span> <span class='kw'>&lt;-</span> <span class='fu'>genotype_curve</span>(<span class='no'>nancycats</span>)</div><div class='output co'>#&gt; 
Calculating genotypes for  1/8 loci. Completed iterations:   1%
Calculating genotypes for  1/8 loci. Completed iterations:   2%
Calculating genotypes for  1/8 loci. Completed iterations:   3%
Calculating genotypes for  1/8 loci. Completed iterations:   4%
Calculating genotypes for  1/8 loci. Completed iterations:   5%
Calculating genotypes for  1/8 loci. Completed iterations:   6%
Calculating genotypes for  1/8 loci. Completed iterations:   7%
Calculating genotypes for  1/8 loci. Completed iterations:   8%
Calculating genotypes for  1/8 loci. Completed iterations:   9%
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Calculating genotypes for  1/8 loci. Completed iterations:  11%
Calculating genotypes for  1/8 loci. Completed iterations:  12%
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Calculating genotypes for  1/8 loci. Completed iterations:  14%
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Calculating genotypes for  1/8 loci. Completed iterations:  17%
Calculating genotypes for  1/8 loci. Completed iterations:  18%
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Calculating genotypes for  1/8 loci. Completed iterations:  20%
Calculating genotypes for  1/8 loci. Completed iterations:  21%
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Calculating genotypes for  1/8 loci. Completed iterations:  27%
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Calculating genotypes for  1/8 loci. Completed iterations:  43%
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Calculating genotypes for  1/8 loci. Completed iterations:  45%
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Calculating genotypes for  1/8 loci. Completed iterations:  48%
Calculating genotypes for  1/8 loci. Completed iterations:  49%
Calculating genotypes for  1/8 loci. Completed iterations:  50%
Calculating genotypes for  1/8 loci. Completed iterations:  51%
Calculating genotypes for  1/8 loci. Completed iterations:  52%
Calculating genotypes for  1/8 loci. Completed iterations:  53%
Calculating genotypes for  1/8 loci. Completed iterations:  54%
Calculating genotypes for  1/8 loci. Completed iterations:  55%
Calculating genotypes for  1/8 loci. Completed iterations:  56%
Calculating genotypes for  1/8 loci. Completed iterations:  57%
Calculating genotypes for  1/8 loci. Completed iterations:  58%
Calculating genotypes for  1/8 loci. Completed iterations:  59%
Calculating genotypes for  1/8 loci. Completed iterations:  60%
Calculating genotypes for  1/8 loci. Completed iterations:  61%
Calculating genotypes for  1/8 loci. Completed iterations:  62%
Calculating genotypes for  1/8 loci. Completed iterations:  63%
Calculating genotypes for  1/8 loci. Completed iterations:  64%
Calculating genotypes for  1/8 loci. Completed iterations:  65%
Calculating genotypes for  1/8 loci. Completed iterations:  66%
Calculating genotypes for  1/8 loci. Completed iterations:  67%
Calculating genotypes for  1/8 loci. Completed iterations:  68%
Calculating genotypes for  1/8 loci. Completed iterations:  69%
Calculating genotypes for  1/8 loci. Completed iterations:  70%
Calculating genotypes for  1/8 loci. Completed iterations:  71%
Calculating genotypes for  1/8 loci. Completed iterations:  72%
Calculating genotypes for  1/8 loci. Completed iterations:  73%
Calculating genotypes for  1/8 loci. Completed iterations:  74%
Calculating genotypes for  1/8 loci. Completed iterations:  75%
Calculating genotypes for  1/8 loci. Completed iterations:  76%
Calculating genotypes for  1/8 loci. Completed iterations:  77%
Calculating genotypes for  1/8 loci. Completed iterations:  78%
Calculating genotypes for  1/8 loci. Completed iterations:  79%
Calculating genotypes for  1/8 loci. Completed iterations:  80%
Calculating genotypes for  1/8 loci. Completed iterations:  81%
Calculating genotypes for  1/8 loci. Completed iterations:  82%
Calculating genotypes for  1/8 loci. Completed iterations:  83%
Calculating genotypes for  1/8 loci. Completed iterations:  84%
Calculating genotypes for  1/8 loci. Completed iterations:  85%
Calculating genotypes for  1/8 loci. Completed iterations:  86%
Calculating genotypes for  1/8 loci. Completed iterations:  87%
Calculating genotypes for  1/8 loci. Completed iterations:  88%
Calculating genotypes for  1/8 loci. Completed iterations:  89%
Calculating genotypes for  1/8 loci. Completed iterations:  90%
Calculating genotypes for  1/8 loci. Completed iterations:  91%
Calculating genotypes for  1/8 loci. Completed iterations:  92%
Calculating genotypes for  1/8 loci. Completed iterations:  93%
Calculating genotypes for  1/8 loci. Completed iterations:  94%
Calculating genotypes for  1/8 loci. Completed iterations:  95%
Calculating genotypes for  1/8 loci. Completed iterations:  96%
Calculating genotypes for  1/8 loci. Completed iterations:  97%
Calculating genotypes for  1/8 loci. Completed iterations:  98%
Calculating genotypes for  1/8 loci. Completed iterations:  99%
Calculating genotypes for  1/8 loci. Completed iterations: 100%
Calculating genotypes for  2/8 loci. Completed iterations:   1%
Calculating genotypes for  2/8 loci. Completed iterations:   2%
Calculating genotypes for  2/8 loci. Completed iterations:   3%
Calculating genotypes for  2/8 loci. Completed iterations:   4%
Calculating genotypes for  2/8 loci. Completed iterations:   5%
Calculating genotypes for  2/8 loci. Completed iterations:   6%
Calculating genotypes for  2/8 loci. Completed iterations:   7%
Calculating genotypes for  2/8 loci. Completed iterations:   8%
Calculating genotypes for  2/8 loci. Completed iterations:   9%
Calculating genotypes for  2/8 loci. Completed iterations:  10%
Calculating genotypes for  2/8 loci. Completed iterations:  11%
Calculating genotypes for  2/8 loci. Completed iterations:  12%
Calculating genotypes for  2/8 loci. Completed iterations:  13%
Calculating genotypes for  2/8 loci. Completed iterations:  14%
Calculating genotypes for  2/8 loci. Completed iterations:  15%
Calculating genotypes for  2/8 loci. Completed iterations:  16%
Calculating genotypes for  2/8 loci. Completed iterations:  17%
Calculating genotypes for  2/8 loci. Completed iterations:  18%
Calculating genotypes for  2/8 loci. Completed iterations:  19%
Calculating genotypes for  2/8 loci. Completed iterations:  20%
Calculating genotypes for  2/8 loci. Completed iterations:  21%
Calculating genotypes for  2/8 loci. Completed iterations:  22%
Calculating genotypes for  2/8 loci. Completed iterations:  23%
Calculating genotypes for  2/8 loci. Completed iterations:  24%
Calculating genotypes for  2/8 loci. Completed iterations:  25%
Calculating genotypes for  2/8 loci. Completed iterations:  26%
Calculating genotypes for  2/8 loci. Completed iterations:  27%
Calculating genotypes for  2/8 loci. Completed iterations:  28%
Calculating genotypes for  2/8 loci. Completed iterations:  29%
Calculating genotypes for  2/8 loci. Completed iterations:  30%
Calculating genotypes for  2/8 loci. Completed iterations:  31%
Calculating genotypes for  2/8 loci. Completed iterations:  32%
Calculating genotypes for  2/8 loci. Completed iterations:  33%
Calculating genotypes for  2/8 loci. Completed iterations:  34%
Calculating genotypes for  2/8 loci. Completed iterations:  35%
Calculating genotypes for  2/8 loci. Completed iterations:  36%
Calculating genotypes for  2/8 loci. Completed iterations:  37%
Calculating genotypes for  2/8 loci. Completed iterations:  38%
Calculating genotypes for  2/8 loci. Completed iterations:  39%
Calculating genotypes for  2/8 loci. Completed iterations:  40%
Calculating genotypes for  2/8 loci. Completed iterations:  41%
Calculating genotypes for  2/8 loci. Completed iterations:  42%
Calculating genotypes for  2/8 loci. Completed iterations:  43%
Calculating genotypes for  2/8 loci. Completed iterations:  44%
Calculating genotypes for  2/8 loci. Completed iterations:  45%
Calculating genotypes for  2/8 loci. Completed iterations:  46%
Calculating genotypes for  2/8 loci. Completed iterations:  47%
Calculating genotypes for  2/8 loci. Completed iterations:  48%
Calculating genotypes for  2/8 loci. Completed iterations:  49%
Calculating genotypes for  2/8 loci. Completed iterations:  50%
Calculating genotypes for  2/8 loci. Completed iterations:  51%
Calculating genotypes for  2/8 loci. Completed iterations:  52%
Calculating genotypes for  2/8 loci. Completed iterations:  53%
Calculating genotypes for  2/8 loci. Completed iterations:  54%
Calculating genotypes for  2/8 loci. Completed iterations:  55%
Calculating genotypes for  2/8 loci. Completed iterations:  56%
Calculating genotypes for  2/8 loci. Completed iterations:  57%
Calculating genotypes for  2/8 loci. Completed iterations:  58%
Calculating genotypes for  2/8 loci. Completed iterations:  59%
Calculating genotypes for  2/8 loci. Completed iterations:  60%
Calculating genotypes for  2/8 loci. Completed iterations:  61%
Calculating genotypes for  2/8 loci. Completed iterations:  62%
Calculating genotypes for  2/8 loci. Completed iterations:  63%
Calculating genotypes for  2/8 loci. Completed iterations:  64%
Calculating genotypes for  2/8 loci. Completed iterations:  65%
Calculating genotypes for  2/8 loci. Completed iterations:  66%
Calculating genotypes for  2/8 loci. Completed iterations:  67%
Calculating genotypes for  2/8 loci. Completed iterations:  68%
Calculating genotypes for  2/8 loci. Completed iterations:  69%
Calculating genotypes for  2/8 loci. Completed iterations:  70%
Calculating genotypes for  2/8 loci. Completed iterations:  71%
Calculating genotypes for  2/8 loci. Completed iterations:  72%
Calculating genotypes for  2/8 loci. Completed iterations:  73%
Calculating genotypes for  2/8 loci. Completed iterations:  74%
Calculating genotypes for  2/8 loci. Completed iterations:  75%
Calculating genotypes for  2/8 loci. Completed iterations:  76%
Calculating genotypes for  2/8 loci. Completed iterations:  77%
Calculating genotypes for  2/8 loci. Completed iterations:  78%
Calculating genotypes for  2/8 loci. Completed iterations:  79%
Calculating genotypes for  2/8 loci. Completed iterations:  80%
Calculating genotypes for  2/8 loci. Completed iterations:  81%
Calculating genotypes for  2/8 loci. Completed iterations:  82%
Calculating genotypes for  2/8 loci. Completed iterations:  83%
Calculating genotypes for  2/8 loci. Completed iterations:  84%
Calculating genotypes for  2/8 loci. Completed iterations:  85%
Calculating genotypes for  2/8 loci. Completed iterations:  86%
Calculating genotypes for  2/8 loci. Completed iterations:  87%
Calculating genotypes for  2/8 loci. Completed iterations:  88%
Calculating genotypes for  2/8 loci. Completed iterations:  89%
Calculating genotypes for  2/8 loci. Completed iterations:  90%
Calculating genotypes for  2/8 loci. Completed iterations:  91%
Calculating genotypes for  2/8 loci. Completed iterations:  92%
Calculating genotypes for  2/8 loci. Completed iterations:  93%
Calculating genotypes for  2/8 loci. Completed iterations:  94%
Calculating genotypes for  2/8 loci. Completed iterations:  95%
Calculating genotypes for  2/8 loci. Completed iterations:  96%
Calculating genotypes for  2/8 loci. Completed iterations:  97%
Calculating genotypes for  2/8 loci. Completed iterations:  98%
Calculating genotypes for  2/8 loci. Completed iterations:  99%
Calculating genotypes for  2/8 loci. Completed iterations: 100%
Calculating genotypes for  3/8 loci. Completed iterations:   1%
Calculating genotypes for  3/8 loci. Completed iterations:   2%
Calculating genotypes for  3/8 loci. Completed iterations:   3%
Calculating genotypes for  3/8 loci. Completed iterations:   4%
Calculating genotypes for  3/8 loci. Completed iterations:   5%
Calculating genotypes for  3/8 loci. Completed iterations:   6%
Calculating genotypes for  3/8 loci. Completed iterations:   7%
Calculating genotypes for  3/8 loci. Completed iterations:   8%
Calculating genotypes for  3/8 loci. Completed iterations:   9%
Calculating genotypes for  3/8 loci. Completed iterations:  10%
Calculating genotypes for  3/8 loci. Completed iterations:  11%
Calculating genotypes for  3/8 loci. Completed iterations:  12%
Calculating genotypes for  3/8 loci. Completed iterations:  13%
Calculating genotypes for  3/8 loci. Completed iterations:  14%
Calculating genotypes for  3/8 loci. Completed iterations:  15%
Calculating genotypes for  3/8 loci. Completed iterations:  16%
Calculating genotypes for  3/8 loci. Completed iterations:  17%
Calculating genotypes for  3/8 loci. Completed iterations:  18%
Calculating genotypes for  3/8 loci. Completed iterations:  19%
Calculating genotypes for  3/8 loci. Completed iterations:  20%
Calculating genotypes for  3/8 loci. Completed iterations:  21%
Calculating genotypes for  3/8 loci. Completed iterations:  22%
Calculating genotypes for  3/8 loci. Completed iterations:  23%
Calculating genotypes for  3/8 loci. Completed iterations:  24%
Calculating genotypes for  3/8 loci. Completed iterations:  25%
Calculating genotypes for  3/8 loci. Completed iterations:  26%
Calculating genotypes for  3/8 loci. Completed iterations:  27%
Calculating genotypes for  3/8 loci. Completed iterations:  28%
Calculating genotypes for  3/8 loci. Completed iterations:  29%
Calculating genotypes for  3/8 loci. Completed iterations:  30%
Calculating genotypes for  3/8 loci. Completed iterations:  31%
Calculating genotypes for  3/8 loci. Completed iterations:  32%
Calculating genotypes for  3/8 loci. Completed iterations:  33%
Calculating genotypes for  3/8 loci. Completed iterations:  34%
Calculating genotypes for  3/8 loci. Completed iterations:  35%
Calculating genotypes for  3/8 loci. Completed iterations:  36%
Calculating genotypes for  3/8 loci. Completed iterations:  37%
Calculating genotypes for  3/8 loci. Completed iterations:  38%
Calculating genotypes for  3/8 loci. Completed iterations:  39%
Calculating genotypes for  3/8 loci. Completed iterations:  40%
Calculating genotypes for  3/8 loci. Completed iterations:  41%
Calculating genotypes for  3/8 loci. Completed iterations:  42%
Calculating genotypes for  3/8 loci. Completed iterations:  43%
Calculating genotypes for  3/8 loci. Completed iterations:  44%
Calculating genotypes for  3/8 loci. Completed iterations:  45%
Calculating genotypes for  3/8 loci. Completed iterations:  46%
Calculating genotypes for  3/8 loci. Completed iterations:  47%
Calculating genotypes for  3/8 loci. Completed iterations:  48%
Calculating genotypes for  3/8 loci. Completed iterations:  49%
Calculating genotypes for  3/8 loci. Completed iterations:  50%
Calculating genotypes for  3/8 loci. Completed iterations:  51%
Calculating genotypes for  3/8 loci. Completed iterations:  52%
Calculating genotypes for  3/8 loci. Completed iterations:  53%
Calculating genotypes for  3/8 loci. Completed iterations:  54%
Calculating genotypes for  3/8 loci. Completed iterations:  55%
Calculating genotypes for  3/8 loci. Completed iterations:  56%
Calculating genotypes for  3/8 loci. Completed iterations:  57%
Calculating genotypes for  3/8 loci. Completed iterations:  58%
Calculating genotypes for  3/8 loci. Completed iterations:  59%
Calculating genotypes for  3/8 loci. Completed iterations:  60%
Calculating genotypes for  3/8 loci. Completed iterations:  61%
Calculating genotypes for  3/8 loci. Completed iterations:  62%
Calculating genotypes for  3/8 loci. Completed iterations:  63%
Calculating genotypes for  3/8 loci. Completed iterations:  64%
Calculating genotypes for  3/8 loci. Completed iterations:  65%
Calculating genotypes for  3/8 loci. Completed iterations:  66%
Calculating genotypes for  3/8 loci. Completed iterations:  67%
Calculating genotypes for  3/8 loci. Completed iterations:  68%
Calculating genotypes for  3/8 loci. Completed iterations:  69%
Calculating genotypes for  3/8 loci. Completed iterations:  70%
Calculating genotypes for  3/8 loci. Completed iterations:  71%
Calculating genotypes for  3/8 loci. Completed iterations:  72%
Calculating genotypes for  3/8 loci. Completed iterations:  73%
Calculating genotypes for  3/8 loci. Completed iterations:  74%
Calculating genotypes for  3/8 loci. Completed iterations:  75%
Calculating genotypes for  3/8 loci. Completed iterations:  76%
Calculating genotypes for  3/8 loci. Completed iterations:  77%
Calculating genotypes for  3/8 loci. Completed iterations:  78%
Calculating genotypes for  3/8 loci. Completed iterations:  79%
Calculating genotypes for  3/8 loci. Completed iterations:  80%
Calculating genotypes for  3/8 loci. Completed iterations:  81%
Calculating genotypes for  3/8 loci. Completed iterations:  82%
Calculating genotypes for  3/8 loci. Completed iterations:  83%
Calculating genotypes for  3/8 loci. Completed iterations:  84%
Calculating genotypes for  3/8 loci. Completed iterations:  85%
Calculating genotypes for  3/8 loci. Completed iterations:  86%
Calculating genotypes for  3/8 loci. Completed iterations:  87%
Calculating genotypes for  3/8 loci. Completed iterations:  88%
Calculating genotypes for  3/8 loci. Completed iterations:  89%
Calculating genotypes for  3/8 loci. Completed iterations:  90%
Calculating genotypes for  3/8 loci. Completed iterations:  91%
Calculating genotypes for  3/8 loci. Completed iterations:  92%
Calculating genotypes for  3/8 loci. Completed iterations:  93%
Calculating genotypes for  3/8 loci. Completed iterations:  94%
Calculating genotypes for  3/8 loci. Completed iterations:  95%
Calculating genotypes for  3/8 loci. Completed iterations:  96%
Calculating genotypes for  3/8 loci. Completed iterations:  97%
Calculating genotypes for  3/8 loci. Completed iterations:  98%
Calculating genotypes for  3/8 loci. Completed iterations:  99%
Calculating genotypes for  3/8 loci. Completed iterations: 100%
Calculating genotypes for  4/8 loci. Completed iterations:   1%
Calculating genotypes for  4/8 loci. Completed iterations:   2%
Calculating genotypes for  4/8 loci. Completed iterations:   3%
Calculating genotypes for  4/8 loci. Completed iterations:   4%
Calculating genotypes for  4/8 loci. Completed iterations:   5%
Calculating genotypes for  4/8 loci. Completed iterations:   6%
Calculating genotypes for  4/8 loci. Completed iterations:   7%
Calculating genotypes for  4/8 loci. Completed iterations:   8%
Calculating genotypes for  4/8 loci. Completed iterations:   9%
Calculating genotypes for  4/8 loci. Completed iterations:  10%
Calculating genotypes for  4/8 loci. Completed iterations:  11%
Calculating genotypes for  4/8 loci. Completed iterations:  12%
Calculating genotypes for  4/8 loci. Completed iterations:  13%
Calculating genotypes for  4/8 loci. Completed iterations:  14%
Calculating genotypes for  4/8 loci. Completed iterations:  15%
Calculating genotypes for  4/8 loci. Completed iterations:  16%
Calculating genotypes for  4/8 loci. Completed iterations:  17%
Calculating genotypes for  4/8 loci. Completed iterations:  18%
Calculating genotypes for  4/8 loci. Completed iterations:  19%
Calculating genotypes for  4/8 loci. Completed iterations:  20%
Calculating genotypes for  4/8 loci. Completed iterations:  21%
Calculating genotypes for  4/8 loci. Completed iterations:  22%
Calculating genotypes for  4/8 loci. Completed iterations:  23%
Calculating genotypes for  4/8 loci. Completed iterations:  24%
Calculating genotypes for  4/8 loci. Completed iterations:  25%
Calculating genotypes for  4/8 loci. Completed iterations:  26%
Calculating genotypes for  4/8 loci. Completed iterations:  27%
Calculating genotypes for  4/8 loci. Completed iterations:  28%
Calculating genotypes for  4/8 loci. Completed iterations:  29%
Calculating genotypes for  4/8 loci. Completed iterations:  30%
Calculating genotypes for  4/8 loci. Completed iterations:  31%
Calculating genotypes for  4/8 loci. Completed iterations:  32%
Calculating genotypes for  4/8 loci. Completed iterations:  33%
Calculating genotypes for  4/8 loci. Completed iterations:  34%
Calculating genotypes for  4/8 loci. Completed iterations:  35%
Calculating genotypes for  4/8 loci. Completed iterations:  36%
Calculating genotypes for  4/8 loci. Completed iterations:  37%
Calculating genotypes for  4/8 loci. Completed iterations:  38%
Calculating genotypes for  4/8 loci. Completed iterations:  39%
Calculating genotypes for  4/8 loci. Completed iterations:  40%
Calculating genotypes for  4/8 loci. Completed iterations:  41%
Calculating genotypes for  4/8 loci. Completed iterations:  42%
Calculating genotypes for  4/8 loci. Completed iterations:  43%
Calculating genotypes for  4/8 loci. Completed iterations:  44%
Calculating genotypes for  4/8 loci. Completed iterations:  45%
Calculating genotypes for  4/8 loci. Completed iterations:  46%
Calculating genotypes for  4/8 loci. Completed iterations:  47%
Calculating genotypes for  4/8 loci. Completed iterations:  48%
Calculating genotypes for  4/8 loci. Completed iterations:  49%
Calculating genotypes for  4/8 loci. Completed iterations:  50%
Calculating genotypes for  4/8 loci. Completed iterations:  51%
Calculating genotypes for  4/8 loci. Completed iterations:  52%
Calculating genotypes for  4/8 loci. Completed iterations:  53%
Calculating genotypes for  4/8 loci. Completed iterations:  54%
Calculating genotypes for  4/8 loci. Completed iterations:  55%
Calculating genotypes for  4/8 loci. Completed iterations:  56%
Calculating genotypes for  4/8 loci. Completed iterations:  57%
Calculating genotypes for  4/8 loci. Completed iterations:  58%
Calculating genotypes for  4/8 loci. Completed iterations:  59%
Calculating genotypes for  4/8 loci. Completed iterations:  60%
Calculating genotypes for  4/8 loci. Completed iterations:  61%
Calculating genotypes for  4/8 loci. Completed iterations:  62%
Calculating genotypes for  4/8 loci. Completed iterations:  63%
Calculating genotypes for  4/8 loci. Completed iterations:  64%
Calculating genotypes for  4/8 loci. Completed iterations:  65%
Calculating genotypes for  4/8 loci. Completed iterations:  66%
Calculating genotypes for  4/8 loci. Completed iterations:  67%
Calculating genotypes for  4/8 loci. Completed iterations:  68%
Calculating genotypes for  4/8 loci. Completed iterations:  69%
Calculating genotypes for  4/8 loci. Completed iterations:  70%
Calculating genotypes for  4/8 loci. Completed iterations:  71%
Calculating genotypes for  4/8 loci. Completed iterations:  72%
Calculating genotypes for  4/8 loci. Completed iterations:  73%
Calculating genotypes for  4/8 loci. Completed iterations:  74%
Calculating genotypes for  4/8 loci. Completed iterations:  75%
Calculating genotypes for  4/8 loci. Completed iterations:  76%
Calculating genotypes for  4/8 loci. Completed iterations:  77%
Calculating genotypes for  4/8 loci. Completed iterations:  78%
Calculating genotypes for  4/8 loci. Completed iterations:  79%
Calculating genotypes for  4/8 loci. Completed iterations:  80%
Calculating genotypes for  4/8 loci. Completed iterations:  81%
Calculating genotypes for  4/8 loci. Completed iterations:  82%
Calculating genotypes for  4/8 loci. Completed iterations:  83%
Calculating genotypes for  4/8 loci. Completed iterations:  84%
Calculating genotypes for  4/8 loci. Completed iterations:  85%
Calculating genotypes for  4/8 loci. Completed iterations:  86%
Calculating genotypes for  4/8 loci. Completed iterations:  87%
Calculating genotypes for  4/8 loci. Completed iterations:  88%
Calculating genotypes for  4/8 loci. Completed iterations:  89%
Calculating genotypes for  4/8 loci. Completed iterations:  90%
Calculating genotypes for  4/8 loci. Completed iterations:  91%
Calculating genotypes for  4/8 loci. Completed iterations:  92%
Calculating genotypes for  4/8 loci. Completed iterations:  93%
Calculating genotypes for  4/8 loci. Completed iterations:  94%
Calculating genotypes for  4/8 loci. Completed iterations:  95%
Calculating genotypes for  4/8 loci. Completed iterations:  96%
Calculating genotypes for  4/8 loci. Completed iterations:  97%
Calculating genotypes for  4/8 loci. Completed iterations:  98%
Calculating genotypes for  4/8 loci. Completed iterations:  99%
Calculating genotypes for  4/8 loci. Completed iterations: 100%
Calculating genotypes for  5/8 loci. Completed iterations:   1%
Calculating genotypes for  5/8 loci. Completed iterations:   2%
Calculating genotypes for  5/8 loci. Completed iterations:   3%
Calculating genotypes for  5/8 loci. Completed iterations:   4%
Calculating genotypes for  5/8 loci. Completed iterations:   5%
Calculating genotypes for  5/8 loci. Completed iterations:   6%
Calculating genotypes for  5/8 loci. Completed iterations:   7%
Calculating genotypes for  5/8 loci. Completed iterations:   8%
Calculating genotypes for  5/8 loci. Completed iterations:   9%
Calculating genotypes for  5/8 loci. Completed iterations:  10%
Calculating genotypes for  5/8 loci. Completed iterations:  11%
Calculating genotypes for  5/8 loci. Completed iterations:  12%
Calculating genotypes for  5/8 loci. Completed iterations:  13%
Calculating genotypes for  5/8 loci. Completed iterations:  14%
Calculating genotypes for  5/8 loci. Completed iterations:  15%
Calculating genotypes for  5/8 loci. Completed iterations:  16%
Calculating genotypes for  5/8 loci. Completed iterations:  17%
Calculating genotypes for  5/8 loci. Completed iterations:  18%
Calculating genotypes for  5/8 loci. Completed iterations:  19%
Calculating genotypes for  5/8 loci. Completed iterations:  20%
Calculating genotypes for  5/8 loci. Completed iterations:  21%
Calculating genotypes for  5/8 loci. Completed iterations:  22%
Calculating genotypes for  5/8 loci. Completed iterations:  23%
Calculating genotypes for  5/8 loci. Completed iterations:  24%
Calculating genotypes for  5/8 loci. Completed iterations:  25%
Calculating genotypes for  5/8 loci. Completed iterations:  26%
Calculating genotypes for  5/8 loci. Completed iterations:  27%
Calculating genotypes for  5/8 loci. Completed iterations:  28%
Calculating genotypes for  5/8 loci. Completed iterations:  29%
Calculating genotypes for  5/8 loci. Completed iterations:  30%
Calculating genotypes for  5/8 loci. Completed iterations:  31%
Calculating genotypes for  5/8 loci. Completed iterations:  32%
Calculating genotypes for  5/8 loci. Completed iterations:  33%
Calculating genotypes for  5/8 loci. Completed iterations:  34%
Calculating genotypes for  5/8 loci. Completed iterations:  35%
Calculating genotypes for  5/8 loci. Completed iterations:  36%
Calculating genotypes for  5/8 loci. Completed iterations:  37%
Calculating genotypes for  5/8 loci. Completed iterations:  38%
Calculating genotypes for  5/8 loci. Completed iterations:  39%
Calculating genotypes for  5/8 loci. Completed iterations:  40%
Calculating genotypes for  5/8 loci. Completed iterations:  41%
Calculating genotypes for  5/8 loci. Completed iterations:  42%
Calculating genotypes for  5/8 loci. Completed iterations:  43%
Calculating genotypes for  5/8 loci. Completed iterations:  44%
Calculating genotypes for  5/8 loci. Completed iterations:  45%
Calculating genotypes for  5/8 loci. Completed iterations:  46%
Calculating genotypes for  5/8 loci. Completed iterations:  47%
Calculating genotypes for  5/8 loci. Completed iterations:  48%
Calculating genotypes for  5/8 loci. Completed iterations:  49%
Calculating genotypes for  5/8 loci. Completed iterations:  50%
Calculating genotypes for  5/8 loci. Completed iterations:  51%
Calculating genotypes for  5/8 loci. Completed iterations:  52%
Calculating genotypes for  5/8 loci. Completed iterations:  53%
Calculating genotypes for  5/8 loci. Completed iterations:  54%
Calculating genotypes for  5/8 loci. Completed iterations:  55%
Calculating genotypes for  5/8 loci. Completed iterations:  56%
Calculating genotypes for  5/8 loci. Completed iterations:  57%
Calculating genotypes for  5/8 loci. Completed iterations:  58%
Calculating genotypes for  5/8 loci. Completed iterations:  59%
Calculating genotypes for  5/8 loci. Completed iterations:  60%
Calculating genotypes for  5/8 loci. Completed iterations:  61%
Calculating genotypes for  5/8 loci. Completed iterations:  62%
Calculating genotypes for  5/8 loci. Completed iterations:  63%
Calculating genotypes for  5/8 loci. Completed iterations:  64%
Calculating genotypes for  5/8 loci. Completed iterations:  65%
Calculating genotypes for  5/8 loci. Completed iterations:  66%
Calculating genotypes for  5/8 loci. Completed iterations:  67%
Calculating genotypes for  5/8 loci. Completed iterations:  68%
Calculating genotypes for  5/8 loci. Completed iterations:  69%
Calculating genotypes for  5/8 loci. Completed iterations:  70%
Calculating genotypes for  5/8 loci. Completed iterations:  71%
Calculating genotypes for  5/8 loci. Completed iterations:  72%
Calculating genotypes for  5/8 loci. Completed iterations:  73%
Calculating genotypes for  5/8 loci. Completed iterations:  74%
Calculating genotypes for  5/8 loci. Completed iterations:  75%
Calculating genotypes for  5/8 loci. Completed iterations:  76%
Calculating genotypes for  5/8 loci. Completed iterations:  77%
Calculating genotypes for  5/8 loci. Completed iterations:  78%
Calculating genotypes for  5/8 loci. Completed iterations:  79%
Calculating genotypes for  5/8 loci. Completed iterations:  80%
Calculating genotypes for  5/8 loci. Completed iterations:  81%
Calculating genotypes for  5/8 loci. Completed iterations:  82%
Calculating genotypes for  5/8 loci. Completed iterations:  83%
Calculating genotypes for  5/8 loci. Completed iterations:  84%
Calculating genotypes for  5/8 loci. Completed iterations:  85%
Calculating genotypes for  5/8 loci. Completed iterations:  86%
Calculating genotypes for  5/8 loci. Completed iterations:  87%
Calculating genotypes for  5/8 loci. Completed iterations:  88%
Calculating genotypes for  5/8 loci. Completed iterations:  89%
Calculating genotypes for  5/8 loci. Completed iterations:  90%
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Calculating genotypes for  8/8 loci. Completed iterations:  89%
Calculating genotypes for  8/8 loci. Completed iterations:  90%
Calculating genotypes for  8/8 loci. Completed iterations:  91%
Calculating genotypes for  8/8 loci. Completed iterations:  92%
Calculating genotypes for  8/8 loci. Completed iterations:  93%
Calculating genotypes for  8/8 loci. Completed iterations:  94%
Calculating genotypes for  8/8 loci. Completed iterations:  95%
Calculating genotypes for  8/8 loci. Completed iterations:  96%
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Calculating genotypes for  8/8 loci. Completed iterations:  98%
Calculating genotypes for  8/8 loci. Completed iterations:  99%
Calculating genotypes for  8/8 loci. Completed iterations: 100%</div><div class='img'><img src='genotype_curve-1.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
 <span class='co'># Marker Type Comparison --------------------------------------------------</span>
 <span class='co'># With AFLP data, it is often necessary to include more markers for resolution</span>
 <span class='fu'>data</span>(<span class='no'>Aeut</span>)
diff --git a/docs/reference/greycurve.html b/docs/reference/greycurve.html
index 93238278..bae38905 100644
--- a/docs/reference/greycurve.html
+++ b/docs/reference/greycurve.html
@@ -153,7 +153,7 @@ <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
     <pre class="examples"><div class='input'><span class='co'># Normal grey curve with an adjustment of 3, an upper limit of 0.8, and</span>
 <span class='co'># weighted towards smaller values.</span>
-<span class='fu'>greycurve</span>()</div><div class='img'><img src='greycurve-3.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
+<span class='fu'>greycurve</span>()</div><div class='img'><img src='greycurve-1.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
 <span class='co'># 1:1 relationship grey curve.</span>
 <span class='fu'>greycurve</span>(<span class='kw'>gadj</span><span class='kw'>=</span><span class='fl'>1</span>, <span class='kw'>glim</span><span class='kw'>=</span><span class='fl'>1</span>:<span class='fl'>0</span>)
 
diff --git a/docs/reference/ia.html b/docs/reference/ia.html
index 70c8d9c3..430dd537 100644
--- a/docs/reference/ia.html
+++ b/docs/reference/ia.html
@@ -343,10 +343,10 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; 0.17207262 0.02178965 </div><div class='input'>
 <span class='co'># Pairwise over all loci:</span>
 <span class='fu'>data</span>(<span class='no'>partial_clone</span>)
-<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>pair.ia</span>(<span class='no'>partial_clone</span>)</div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='img'><img src='ia-5.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='fu'>plot</span>(<span class='no'>res</span>, <span class='kw'>low</span> <span class='kw'>=</span> <span class='st'>"black"</span>, <span class='kw'>high</span> <span class='kw'>=</span> <span class='st'>"green"</span>, <span class='kw'>index</span> <span class='kw'>=</span> <span class='st'>"Ia"</span>)</div><div class='img'><img src='ia-6.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>pair.ia</span>(<span class='no'>partial_clone</span>)</div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='img'><img src='ia-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='fu'>plot</span>(<span class='no'>res</span>, <span class='kw'>low</span> <span class='kw'>=</span> <span class='st'>"black"</span>, <span class='kw'>high</span> <span class='kw'>=</span> <span class='st'>"green"</span>, <span class='kw'>index</span> <span class='kw'>=</span> <span class='st'>"Ia"</span>)</div><div class='img'><img src='ia-2.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 <span class='co'># Resampling</span>
 <span class='fu'>data</span>(<span class='no'>Pinf</span>)
-<span class='fu'>resample.ia</span>(<span class='no'>Pinf</span>, <span class='kw'>reps</span> <span class='kw'>=</span> <span class='fl'>99</span>)</div><div class='output co'>#&gt; 
|===============                                       | 29% ~0 s remaining     
|===============================                       | 59% ~0 s remaining     
|==============================================        | 86% ~0 s remaining     </div><div class='output co'>#&gt;           Ia      rbarD
+<span class='fu'>resample.ia</span>(<span class='no'>Pinf</span>, <span class='kw'>reps</span> <span class='kw'>=</span> <span class='fl'>99</span>)</div><div class='output co'>#&gt; 
|================                                      | 31% ~0 s remaining     
|===============================                       | 59% ~0 s remaining     
|===================================================   | 95% ~0 s remaining     </div><div class='output co'>#&gt;           Ia      rbarD
 #&gt; 1  0.6191763 0.06783205
 #&gt; 2  0.6798527 0.07473909
 #&gt; 3  0.5200972 0.05695292
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 0c2b5cb8..1018756e 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -100,7 +100,7 @@
     <div class="page-header">
       <h1>
         Reference
-        <small>version&nbsp;2.6.1</small>
+        <small>version&nbsp;2.7.1</small>
       </h1>
     </div>
 
@@ -134,7 +134,7 @@ <h2 id="section-data-import-export-" class="hasAnchor"><a href="#section-data-im
         </tr><tr>
           <!--  -->
           <td>
-            <p><code><a href="coercion-methods.html">bootgen2genind</a></code> <code><a href="coercion-methods.html">as.genclone</a></code> <code><a href="coercion-methods.html">genclone2genind</a></code> </p>
+            <p><code><a href="coercion-methods.html">bootgen2genind</a></code> <code><a href="coercion-methods.html">as.genclone</a></code> <code><a href="coercion-methods.html">genclone2genind</a></code> <code><a href="coercion-methods.html">as.genambig</a></code> </p>
           </td>
           <td><p>Switch between genind and genclone objects.</p></td>
         </tr><tr>
@@ -168,7 +168,7 @@ <h2 id="section-data-manipulation-" class="hasAnchor"><a href="#section-data-man
         <tr>
           <!--  -->
           <td>
-            <p><code><a href="coercion-methods.html">bootgen2genind</a></code> <code><a href="coercion-methods.html">as.genclone</a></code> <code><a href="coercion-methods.html">genclone2genind</a></code> </p>
+            <p><code><a href="coercion-methods.html">bootgen2genind</a></code> <code><a href="coercion-methods.html">as.genclone</a></code> <code><a href="coercion-methods.html">genclone2genind</a></code> <code><a href="coercion-methods.html">as.genambig</a></code> </p>
           </td>
           <td><p>Switch between genind and genclone objects.</p></td>
         </tr><tr>
@@ -215,6 +215,12 @@ <h2 id="section-data-manipulation-" class="hasAnchor"><a href="#section-data-man
             <p><code><a href="recode_polyploids.html">recode_polyploids</a></code> </p>
           </td>
           <td><p>Recode polyploid microsatellite data for use in frequency based statistics.</p></td>
+        </tr><tr>
+          <!--  -->
+          <td>
+            <p><code><a href="make_haplotypes.html">make_haplotypes</a></code> </p>
+          </td>
+          <td><p>Split samples from a genind object into pseudo-haplotypes</p></td>
         </tr><tr>
           <!--  -->
           <td>
diff --git a/docs/reference/info_table.html b/docs/reference/info_table.html
index 5cae1068..fce503b9 100644
--- a/docs/reference/info_table.html
+++ b/docs/reference/info_table.html
@@ -204,8 +204,8 @@ <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
     <pre class="examples"><div class='input'><span class='fu'>data</span>(<span class='no'>nancycats</span>)
-<span class='no'>nancy.miss</span> <span class='kw'>&lt;-</span> <span class='fu'>info_table</span>(<span class='no'>nancycats</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"missing"</span>)</div><div class='img'><img src='info_table-5.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='fu'>data</span>(<span class='no'>Pinf</span>)
-<span class='no'>Pinf.ploid</span> <span class='kw'>&lt;-</span> <span class='fu'>info_table</span>(<span class='no'>Pinf</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"ploidy"</span>)</div><div class='img'><img src='info_table-6.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='no'>nancy.miss</span> <span class='kw'>&lt;-</span> <span class='fu'>info_table</span>(<span class='no'>nancycats</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"missing"</span>)</div><div class='img'><img src='info_table-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='fu'>data</span>(<span class='no'>Pinf</span>)
+<span class='no'>Pinf.ploid</span> <span class='kw'>&lt;-</span> <span class='fu'>info_table</span>(<span class='no'>Pinf</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"ploidy"</span>)</div><div class='img'><img src='info_table-2.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 </div></pre>
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
diff --git a/docs/reference/make_haplotypes-1.png b/docs/reference/make_haplotypes-1.png
new file mode 100644
index 00000000..0990daab
Binary files /dev/null and b/docs/reference/make_haplotypes-1.png differ
diff --git a/docs/reference/make_haplotypes.html b/docs/reference/make_haplotypes.html
new file mode 100644
index 00000000..7cd5e37b
--- /dev/null
+++ b/docs/reference/make_haplotypes.html
@@ -0,0 +1,293 @@
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+    <div class="page-header">
+    <h1>Split samples from a genind object into pseudo-haplotypes</h1>
+    </div>
+
+    
+    <p>Split samples from a genind object into pseudo-haplotypes</p>
+    
+
+    <pre class="usage"><span class='fu'>make_haplotypes</span>(<span class='no'>gid</span>)</pre>
+    
+    <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
+    <table class="ref-arguments">
+    <colgroup><col class="name" /><col class="desc" /></colgroup>
+    <tr>
+      <th>gid</th>
+      <td><p>a <a href='http://www.rdocumentation.org/packages/adegenet/topics/new.genind'>genind</a> object.</p></td>
+    </tr>
+    </table>
+    
+    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+    <p>a haploid genind object with an extra <a href='http://www.rdocumentation.org/packages/adegenet/topics/strata-methods'>strata</a>
+column called "Individual".</p>
+    
+    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
+
+    <p>Certain analyses, such as <a href='poppr.amova.html'>amova</a> work best if within-sample
+variance (error) can be estimated. Practically, this is performed by
+splitting the genotypes across all loci to create multiple haplotypes. This
+way, the within-sample distance can be calculated and incorporated into the
+model. Please note that the haplotypes generated are based on the order of
+the unphased alleles in the genind object and do not represent true
+haplotypes.</p>
+<p>Haploid data will be returned un-touched.</p>
+    
+    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
+
+    <p>The <a href='http://www.rdocumentation.org/packages/adegenet/topics/accessors'>other slot</a> will not be copied over to the new
+genind object.</p>
+    
+    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
+
+    <p><code><a href='poppr.amova.html'>poppr.amova()</a></code> <code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>pegas::amova()</a></code> <code><a href='coercion-methods.html'>as.genambig()</a></code></p>
+    
+
+    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
+    <pre class="examples"><div class='input'><span class='co'># Diploid data is doubled -------------------------------------------------</span>
+
+<span class='fu'>data</span>(<span class='no'>nancycats</span>)
+<span class='no'>nan9</span> <span class='kw'>&lt;-</span> <span class='no'>nancycats</span>[<span class='kw'>pop</span> <span class='kw'>=</span> <span class='fl'>9</span>]
+<span class='no'>nan9hap</span> <span class='kw'>&lt;-</span> <span class='fu'>make_haplotypes</span>(<span class='no'>nan9</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: No strata found... creating one from the population.</span></div><div class='input'><span class='no'>nan9</span>              <span class='co'># 9 individuals from population 9</span></div><div class='output co'>#&gt; /// GENIND OBJECT /////////
+#&gt; 
+#&gt;  // 9 individuals; 9 loci; 108 alleles; size: 26.2 Kb
+#&gt; 
+#&gt;  // Basic content
+#&gt;    @tab:  9 x 108 matrix of allele counts
+#&gt;    @loc.n.all: number of alleles per locus (range: 8-18)
+#&gt;    @loc.fac: locus factor for the 108 columns of @tab
+#&gt;    @all.names: list of allele names for each locus
+#&gt;    @ploidy: ploidy of each individual  (range: 2-2)
+#&gt;    @type:  codom
+#&gt;    @call: .local(x = x, i = i, j = j, pop = 9, drop = drop)
+#&gt; 
+#&gt;  // Optional content
+#&gt;    @pop: population of each individual (group size range: 9-9)
+#&gt;    @other: a list containing: xy 
+#&gt; </div><div class='input'><span class='no'>nan9hap</span>           <span class='co'># 18 haplotypes</span></div><div class='output co'>#&gt; /// GENIND OBJECT /////////
+#&gt; 
+#&gt;  // 18 individuals; 9 loci; 43 alleles; size: 19.6 Kb
+#&gt; 
+#&gt;  // Basic content
+#&gt;    @tab:  18 x 43 matrix of allele counts
+#&gt;    @loc.n.all: number of alleles per locus (range: 3-8)
+#&gt;    @loc.fac: locus factor for the 43 columns of @tab
+#&gt;    @all.names: list of allele names for each locus
+#&gt;    @ploidy: ploidy of each individual  (range: 1-1)
+#&gt;    @type:  codom
+#&gt;    @call: df2genind(X = newdf, ploidy = 1, strata = df)
+#&gt; 
+#&gt;  // Optional content
+#&gt;    @pop: population of each individual (group size range: 2-2)
+#&gt;    @strata: a data frame with 2 columns ( pop, Individual )</div><div class='input'><span class='fu'>strata</span>(<span class='no'>nan9hap</span>)   <span class='co'># strata gains a new column: Individual</span></div><div class='output co'>#&gt;    pop Individual
+#&gt; 01 P09       N104
+#&gt; 02 P09       N104
+#&gt; 03 P09       N105
+#&gt; 04 P09       N105
+#&gt; 05 P09       N106
+#&gt; 06 P09       N106
+#&gt; 07 P09       N107
+#&gt; 08 P09       N107
+#&gt; 09 P09       N108
+#&gt; 10 P09       N108
+#&gt; 11 P09       N109
+#&gt; 12 P09       N109
+#&gt; 13 P09       N111
+#&gt; 14 P09       N111
+#&gt; 15 P09       N112
+#&gt; 16 P09       N112
+#&gt; 17 P09       N113
+#&gt; 18 P09       N113</div><div class='input'><span class='fu'>indNames</span>(<span class='no'>nan9hap</span>) <span class='co'># individuals are renamed sequentially</span></div><div class='output co'>#&gt;  [1] "01" "02" "03" "04" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14" "15"
+#&gt; [16] "16" "17" "18"</div><div class='input'>
+
+<span class='co'># Mix ploidy data can be split, but should be treated with caution --------</span>
+<span class='co'># </span>
+<span class='co'># For example, the Pinf data set contains 86 tetraploid individuals, </span>
+<span class='co'># but there appear to only be diploids and triploid genotypes. When </span>
+<span class='co'># we convert to haplotypes, those with all missing data are dropped.</span>
+<span class='fu'>data</span>(<span class='no'>Pinf</span>)
+<span class='no'>Pinf</span></div><div class='output co'>#&gt; 
+#&gt; This is a genclone object
+#&gt; -------------------------
+#&gt; Genotype information:
+#&gt; 
+#&gt;    72 multilocus genotypes 
+#&gt;    86 tetraploid individuals
+#&gt;    11 codominant loci
+#&gt; 
+#&gt; Population information:
+#&gt; 
+#&gt;     2 strata - Continent, Country
+#&gt;     2 populations defined - South America, North America</div><div class='input'><span class='no'>pmiss</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='info_table.html'>info_table</a></span>(<span class='no'>Pinf</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"ploidy"</span>, <span class='kw'>plot</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='img'><img src='make_haplotypes-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='co'># No samples appear to be triploid across all loci. This will cause</span>
+<span class='co'># several haplotypes to have a lot of missing data.</span>
+<span class='no'>p_haps</span> <span class='kw'>&lt;-</span> <span class='fu'>make_haplotypes</span>(<span class='no'>Pinf</span>)
+<span class='no'>p_haps</span></div><div class='output co'>#&gt; /// GENIND OBJECT /////////
+#&gt; 
+#&gt;  // 203 individuals; 11 loci; 95 alleles; size: 131.1 Kb
+#&gt; 
+#&gt;  // Basic content
+#&gt;    @tab:  203 x 95 matrix of allele counts
+#&gt;    @loc.n.all: number of alleles per locus (range: 2-25)
+#&gt;    @loc.fac: locus factor for the 95 columns of @tab
+#&gt;    @all.names: list of allele names for each locus
+#&gt;    @ploidy: ploidy of each individual  (range: 1-1)
+#&gt;    @type:  codom
+#&gt;    @call: df2genind(X = newdf, ploidy = 1, strata = df)
+#&gt; 
+#&gt;  // Optional content
+#&gt;    @pop: population of each individual (group size range: 2-3)
+#&gt;    @strata: a data frame with 3 columns ( Continent, Country, Individual )</div><div class='input'><span class='fu'>head</span>(<span class='fu'>genind2df</span>(<span class='no'>p_haps</span>), <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>20</span>)</div><div class='output co'>#&gt;       pop Pi02  D13 Pi33 Pi04 Pi4B Pi16  G11 Pi56 Pi63 Pi70 Pi89
+#&gt; 2  PiCO01 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;  205 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;
+#&gt; 3  PiCO01  162  136  203  166  213  178  156  174  157  192  179
+#&gt; 4  PiCO01  162  136  203  170  217  178  156  176  157  192  181
+#&gt; 6  PiCO02 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;  205 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;
+#&gt; 7  PiCO02  162  132  203  166  213  178  156  174  157  192  179
+#&gt; 8  PiCO02  162  136  203  170  217  178  156  176  157  192  181
+#&gt; 10 PiCO03 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;  205 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;
+#&gt; 11 PiCO03  162  136  203  166  213  178  156  174  157  192  179
+#&gt; 12 PiCO03  162  136  203  170  217  178  156  176  157  192  181
+#&gt; 14 PiCO04 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;  205 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;
+#&gt; 15 PiCO04  162  136  203  166  213  178  156  174  157  192  179
+#&gt; 16 PiCO04  162  136  203  170  217  178  156  176  157  192  181
+#&gt; 19 PiCO05  160  108  203  166  213  174  156  176  157  192  181
+#&gt; 20 PiCO05  162  112  203  170  225  178  156  176  157  192  181
+#&gt; 23 PiEC01  162  134  203  166  213  178  156  174  157  192  179
+#&gt; 24 PiEC01  162  136  203  170  217  178  156  176  157  192  181
+#&gt; 26 PiEC02 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;  205 &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt; &lt;NA&gt;
+#&gt; 27 PiEC02  162  136  203  166  213  178  156  174  157  192  179
+#&gt; 28 PiEC02  162  144  203  170  217  178  156  176  157  192  181
+#&gt; 31 PiEC03  162  136  203  166  205  178  156  174  157  192  179</div></pre>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
+    <h2>Contents</h2>
+    <ul class="nav nav-pills nav-stacked">
+      <li><a href="#arguments">Arguments</a></li>
+      
+      <li><a href="#value">Value</a></li>
+
+      <li><a href="#details">Details</a></li>
+
+      <li><a href="#note">Note</a></li>
+
+      <li><a href="#see-also">See also</a></li>
+      
+      <li><a href="#examples">Examples</a></li>
+    </ul>
+
+  </div>
+</div>
+
+      <footer>
+      <div class="copyright">
+  <p>Developed by Zhian N. Kamvar, Javier F. Tabima, Jonah C. Brooks.</p>
+</div>
+
+<div class="pkgdown">
+  <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
+</div>
+
+      </footer>
+   </div>
+
+  </body>
+</html>
diff --git a/docs/reference/mlg.html b/docs/reference/mlg.html
index 008d232b..99b0c128 100644
--- a/docs/reference/mlg.html
+++ b/docs/reference/mlg.html
@@ -291,7 +291,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; [163]  90  80  99  88  80  77  78  77  87  80  91 101  79 102  78 103 103  95
 #&gt; [181]  97  81  80  97  97  97 101</div><div class='input'>
 <span class='co'># Get a table</span>
-<span class='no'>atab</span> <span class='kw'>&lt;-</span> <span class='fu'>mlg.table</span>(<span class='no'>Aeut</span>, <span class='kw'>color</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='img'><img src='mlg-3.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='no'>atab</span></div><div class='output co'>#&gt;            MLG.1 MLG.2 MLG.3 MLG.4 MLG.5 MLG.6 MLG.7 MLG.8 MLG.9 MLG.10 MLG.11
+<span class='no'>atab</span> <span class='kw'>&lt;-</span> <span class='fu'>mlg.table</span>(<span class='no'>Aeut</span>, <span class='kw'>color</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='img'><img src='mlg-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='no'>atab</span></div><div class='output co'>#&gt;            MLG.1 MLG.2 MLG.3 MLG.4 MLG.5 MLG.6 MLG.7 MLG.8 MLG.9 MLG.10 MLG.11
 #&gt; Athena         1     0     0     0     0     0     1     1     1      1      1
 #&gt; Mt. Vernon     0     2     1     1     1     1     0     0     0      0      0
 #&gt;            MLG.12 MLG.13 MLG.14 MLG.15 MLG.16 MLG.17 MLG.18 MLG.19 MLG.20
diff --git a/docs/reference/plot_poppr_msn-1.png b/docs/reference/plot_poppr_msn-1.png
index dc91f7e5..40dd3272 100644
Binary files a/docs/reference/plot_poppr_msn-1.png and b/docs/reference/plot_poppr_msn-1.png differ
diff --git a/docs/reference/plot_poppr_msn.html b/docs/reference/plot_poppr_msn.html
index 51810cca..fabfa64a 100644
--- a/docs/reference/plot_poppr_msn.html
+++ b/docs/reference/plot_poppr_msn.html
@@ -320,9 +320,17 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='no'>amsn</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='poppr.msn.html'>poppr.msn</a></span>(<span class='no'>Aeut</span>, <span class='no'>adist</span>, <span class='kw'>showplot</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
 
 <span class='co'># Default</span>
-<span class='fu'>library</span>(<span class='st'>"igraph"</span>) <span class='co'># To get all the layouts.</span>
-<span class='fu'>set.seed</span>(<span class='fl'>500</span>)
-<span class='fu'>plot_poppr_msn</span>(<span class='no'>Aeut</span>, <span class='no'>amsn</span>, <span class='kw'>gadj</span> <span class='kw'>=</span> <span class='fl'>15</span>)</div><div class='img'><img src='plot_poppr_msn-3.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='fu'>library</span>(<span class='st'>"igraph"</span>) <span class='co'># To get all the layouts.</span></div><div class='output co'>#&gt; <span class='message'></span>
+#&gt; <span class='message'>Attaching package: ‘igraph’</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:poppr’:</span>
+#&gt; <span class='message'></span>
+#&gt; <span class='message'>    diversity</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:testthat’:</span>
+#&gt; <span class='message'></span>
+#&gt; <span class='message'>    compare</span></div><div class='output co'>#&gt; <span class='message'>The following objects are masked from ‘package:stats’:</span>
+#&gt; <span class='message'></span>
+#&gt; <span class='message'>    decompose, spectrum</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:base’:</span>
+#&gt; <span class='message'></span>
+#&gt; <span class='message'>    union</span></div><div class='input'><span class='fu'>set.seed</span>(<span class='fl'>500</span>)
+<span class='fu'>plot_poppr_msn</span>(<span class='no'>Aeut</span>, <span class='no'>amsn</span>, <span class='kw'>gadj</span> <span class='kw'>=</span> <span class='fl'>15</span>)</div><div class='img'><img src='plot_poppr_msn-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 </div><span class='co'># NOT RUN {</span>
 <span class='co'># Different layouts (from igraph) can be used by supplying the function name.</span>
 <span class='fu'>set.seed</span>(<span class='fl'>500</span>)
diff --git a/docs/reference/poppr.amova.html b/docs/reference/poppr.amova.html
index 2398f431..7e54c212 100644
--- a/docs/reference/poppr.amova.html
+++ b/docs/reference/poppr.amova.html
@@ -104,73 +104,79 @@ <h1>Perform Analysis of Molecular Variance (AMOVA) on genind or genclone objects
     
     <p>This function simplifies the process necessary for performing AMOVA in R. It
 gives user the choice of utilizing either the <span class="pkg">ade4</span> or the <span class="pkg">pegas</span>
-implementation of AMOVA. See <code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>amova</a></code> (ade4) and
-<code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>amova</a></code> (pegas) for details on the specific
-implementation.</p>
+implementation of AMOVA. See <code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>ade4::amova()</a></code> (ade4) and <code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>pegas::amova()</a></code>
+(pegas) for details on the specific implementation.</p>
     
 
     <pre class="usage"><span class='fu'>poppr.amova</span>(<span class='no'>x</span>, <span class='kw'>hier</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>clonecorrect</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>within</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
-  <span class='kw'>dist</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>squared</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>correction</span> <span class='kw'>=</span> <span class='st'>"quasieuclid"</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"_"</span>,
-  <span class='kw'>filter</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0</span>, <span class='kw'>algorithm</span> <span class='kw'>=</span> <span class='st'>"farthest_neighbor"</span>,
-  <span class='kw'>missing</span> <span class='kw'>=</span> <span class='st'>"loci"</span>, <span class='kw'>cutoff</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"ade4"</span>,
-  <span class='st'>"pegas"</span>), <span class='kw'>nperm</span> <span class='kw'>=</span> <span class='fl'>0</span>)</pre>
+  <span class='kw'>dist</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>squared</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>freq</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>correction</span> <span class='kw'>=</span> <span class='st'>"quasieuclid"</span>,
+  <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"_"</span>, <span class='kw'>filter</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0</span>,
+  <span class='kw'>algorithm</span> <span class='kw'>=</span> <span class='st'>"farthest_neighbor"</span>, <span class='kw'>missing</span> <span class='kw'>=</span> <span class='st'>"loci"</span>, <span class='kw'>cutoff</span> <span class='kw'>=</span> <span class='fl'>0.05</span>,
+  <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"ade4"</span>, <span class='st'>"pegas"</span>), <span class='kw'>nperm</span> <span class='kw'>=</span> <span class='fl'>0</span>)</pre>
     
     <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
     <table class="ref-arguments">
     <colgroup><col class="name" /><col class="desc" /></colgroup>
     <tr>
       <th>x</th>
-      <td><p>a <code>genind</code> or <code><a href='genclone-class.html'>genclone</a></code>
-object</p></td>
+      <td><p>a genind or <a href='genclone-class.html'>genclone</a> object</p></td>
     </tr>
     <tr>
       <th>hier</th>
-      <td><p>a hierarchical <code>formula</code> that defines your population
-hierarchy. (e.g.: ~Population/Subpopulation). <strong>See Details below.</strong></p></td>
+      <td><p>a hierarchical formula that defines your population
+hierarchy. (e.g.: <code>~Population/Subpopulation</code>). <strong>See Details below</strong>.</p></td>
     </tr>
     <tr>
       <th>clonecorrect</th>
-      <td><p><code>logical</code> if <code>TRUE</code>, the data set will be clone
-corrected with respect to the lowest level of the hierarchy. The default is
-set to <code>FALSE</code>. See <code><a href='clonecorrect.html'>clonecorrect</a></code> for details.</p></td>
+      <td><p><code>logical</code> if <code>TRUE</code>, the data set will be clone corrected
+with respect to the lowest level of the hierarchy. The default is set to
+<code>FALSE</code>. See <code><a href='clonecorrect.html'>clonecorrect()</a></code> for details.</p></td>
     </tr>
     <tr>
       <th>within</th>
-      <td><p><code>logical</code>. When this is set to <code>TRUE</code> (Default), 
-variance within individuals are calculated as well. If this is set to
-<code>FALSE</code>, The lowest level of the hierarchy will be the sample level.
-See Details below.</p></td>
+      <td><p><code>logical</code>. When this is set to <code>TRUE</code> (Default), variance
+within individuals are calculated as well. If this is set to <code>FALSE</code>, The
+lowest level of the hierarchy will be the sample level. See Details below.</p></td>
     </tr>
     <tr>
       <th>dist</th>
       <td><p>an optional distance matrix calculated on your data. If this is
-set to <code>NULL</code> (default), the raw pairwise distances will be calculated
-via <code><a href='diss.dist.html'>diss.dist</a></code>.</p></td>
+set to <code>NULL</code> (default), the raw pairwise distances will be calculated via
+<code>dist()</code>.</p></td>
     </tr>
     <tr>
       <th>squared</th>
       <td><p>if a distance matrix is supplied, this indicates whether or
 not it represents squared distances.</p></td>
+    </tr>
+    <tr>
+      <th>freq</th>
+      <td><p><code>logical</code>. If <code>within = FALSE</code>, the parameter rho is calculated
+(Ronfort et al. 1998; Meirmans and Liu 2018). By setting <code>freq = TRUE</code>,
+(default) allele counts will be converted to frequencies before the
+distance is calculated, otherwise, the distance will be calculated on
+allele counts, which can bias results in mixed-ploidy data sets. Note that
+this option has no effect for haploid or presence/absence data sets.</p></td>
     </tr>
     <tr>
       <th>correction</th>
-      <td><p>a <code>character</code> defining the correction method for 
-non-euclidean distances. Options are <code><a href='http://www.rdocumentation.org/packages/ade4/topics/quasieuclid'>quasieuclid</a></code>
-(Default), <code><a href='http://www.rdocumentation.org/packages/ade4/topics/lingoes'>lingoes</a></code>, and <code><a href='http://www.rdocumentation.org/packages/ade4/topics/cailliez'>cailliez</a></code>.
-See Details below.</p></td>
+      <td><p>a <code>character</code> defining the correction method for
+non-euclidean distances. Options are <code><a href='http://www.rdocumentation.org/packages/ade4/topics/quasieuclid'>ade4::quasieuclid()</a></code> (Default),
+<code><a href='http://www.rdocumentation.org/packages/ade4/topics/lingoes'>ade4::lingoes()</a></code>, and <code><a href='http://www.rdocumentation.org/packages/ade4/topics/cailliez'>ade4::cailliez()</a></code>. See Details below.</p></td>
     </tr>
     <tr>
       <th>sep</th>
-      <td><p>Deprecated. As of poppr version 2, this argument serves no purpose.</p></td>
+      <td><p>Deprecated. As of poppr version 2, this argument serves no
+purpose.</p></td>
     </tr>
     <tr>
       <th>filter</th>
-      <td><p><code>logical</code> When set to <code>TRUE</code>, mlg.filter will be run 
-to determine genotypes from the distance matrix. It defaults to 
-<code>FALSE</code>. You can set the parameters with <code>algorithm</code> and
-<code>threshold</code> arguments. Note that this will not be performed when 
-<code>within = TRUE</code>. Note that the threshold should be the number of
-allowable substitutions if you don't supply a distance matrix.</p></td>
+      <td><p><code>logical</code> When set to <code>TRUE</code>, mlg.filter will be run to
+determine genotypes from the distance matrix. It defaults to <code>FALSE</code>. You
+can set the parameters with <code>algorithm</code> and <code>threshold</code> arguments. Note
+that this will not be performed when <code>within = TRUE</code>. Note that the
+threshold should be the number of allowable substitutions if you don't
+supply a distance matrix.</p></td>
     </tr>
     <tr>
       <th>threshold</th>
@@ -193,23 +199,22 @@ <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Ar
     <tr>
       <th>missing</th>
       <td><p>specify method of correcting for missing data utilizing
-options given in the function <code><a href='missingno.html'>missingno</a></code>. Default is
-<code>"loci"</code>.</p></td>
+options given in the function <code><a href='missingno.html'>missingno()</a></code>. Default is <code>"loci"</code>.</p></td>
     </tr>
     <tr>
       <th>cutoff</th>
       <td><p>specify the level at which missing data should be
-removed/modified. See <code><a href='missingno.html'>missingno</a></code> for details.</p></td>
+removed/modified. See <code><a href='missingno.html'>missingno()</a></code> for details.</p></td>
     </tr>
     <tr>
       <th>quiet</th>
       <td><p><code>logical</code> If <code>FALSE</code> (Default), messages regarding any
-corrections will be printed to the screen. If <code>TRUE</code>, no messages will
-be printed.</p></td>
+corrections will be printed to the screen. If <code>TRUE</code>, no messages will be
+printed.</p></td>
     </tr>
     <tr>
       <th>method</th>
-      <td><p>Which method for calculating AMOVA should be used? Choices 
+      <td><p>Which method for calculating AMOVA should be used? Choices
 refer to package implementations: "ade4" (default) or "pegas". See details
 for differences.</p></td>
     </tr>
@@ -222,79 +227,88 @@ <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Ar
     
     <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
 
-    <p>a list of class <code>amova</code> from the ade4 package. See 
-  <code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>amova</a></code> for details.</p>
+    <p>a list of class <code>amova</code> from the ade4 or pegas package. See
+<code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>ade4::amova()</a></code> or <code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>pegas::amova()</a></code> for details.</p>
     
     <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
 
     <p>The poppr implementation of AMOVA is a very detailed wrapper for the
-  ade4 implementation. The output is an <code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>amova</a></code> class list 
-  that contains the results in the first four elements. The inputs are
-  contained in the last three elements. The inputs required for the ade4
-  implementation are:</p><ol>
+ade4 implementation. The output is an <code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>ade4::amova()</a></code> class list that
+contains the results in the first four elements. The inputs are contained
+in the last three elements. The inputs required for the ade4 implementation
+are:</p><ol>
 <li><p>a distance matrix on all unique genotypes (haplotypes)</p></li>
 <li><p>a data frame defining the hierarchy of the distance matrix</p></li>
 <li><p>a genotype (haplotype) frequency table.</p></li>
-</ol><p>All of this data can be constructed from a <code>genind</code>
-  object, but can be daunting for a novice R user. <em>This function
-  automates the entire process</em>. Since there are many variables regarding
-  genetic data, some points need to be highlighted:</p>  
-<p></p><h3>On Hierarchies:</h3>
-The hierarchy is defined by different 
-  population strata that separate your data hierarchically. These strata are
-  defined in the <strong>strata</strong> slot of <code>genind</code> and
-  <code><a href='genclone-class.html'>genclone</a></code><p>objects. They are useful for defining the
-  population factor for your data. See the function <code>strata</code> for
-  details on how to properly define these strata.</p>
-<p></p><h3>On Within Individual Variance:</h3>
+</ol>
+    <p>All of this data can be constructed from a genind object,
+but can be daunting for a novice R user. <em>This function automates the
+entire process</em>. Since there are many variables regarding genetic data,
+some points need to be highlighted:</p><h3>On Hierarchies:</h3>
+The hierarchy is defined by different
+population strata that separate your data hierarchically. These strata are
+defined in the <strong>strata</strong> slot of genind and
+<a href='genclone-class.html'>genclone</a> objects. They are useful for defining the
+population factor for your data. See the function <code>strata()</code> for details on
+how to properly define these strata.
+    <h3>On Within Individual Variance:</h3>
  Heterozygosities within
-  diploid genotypes are sources of variation from within individuals and can
-  be quantified in AMOVA. When <code>within = TRUE</code>, poppr will split diploid
-  genotypes into haplotypes and use those to calculate within-individual 
-  variance. No estimation of phase is made. This acts much like the default 
-  settings for AMOVA in the Arlequin software package. Within individual 
-  variance will not be calculated for haploid individuals or dominant 
-  markers.
-    <p></p><h3>On Euclidean Distances:</h3>
- AMOVA, as defined by
-  Excoffier et al., utilizes an absolute genetic distance measured in the
-  number of differences between two samples across all loci. With the ade4
-  implementation of AMOVA (utilized by poppr), distances must be Euclidean
-  (due to the nature of the calculations). Unfortunately, many genetic
-  distance measures are not always euclidean and must be corrected for before
-  being analyzed. Poppr automates this with three methods implemented in 
-  ade4, <code>quasieuclid</code>, <code>lingoes</code>, and 
-  <code>cailliez</code>. The correction of these distances should not 
-  adversely affect the outcome of the analysis.
-    <p></p><h3>On Filtering:</h3>
+genotypes are sources of variation from within individuals and can be
+quantified in AMOVA. When <code>within = TRUE</code>, poppr will split genotypes into
+haplotypes with the function <code><a href='make_haplotypes.html'>make_haplotypes()</a></code> and use those to calculate
+within-individual variance. No estimation of phase is made. This acts much
+like the default settings for AMOVA in the Arlequin software package.
+Within individual variance will not be calculated for haploid individuals
+or dominant markers as the haplotypes cannot be split further. Setting
+<code>within = FALSE</code> uses the euclidean distance of the allele frequencies
+within each individual
+    <h3>On Euclidean Distances:</h3>
+ With the ade4 implementation of AMOVA
+(utilized by poppr), distances must be Euclidean (due to the nature of the
+calculations). Unfortunately, many genetic distance measures are not always
+euclidean and must be corrected for before being analyzed. Poppr automates
+this with three methods implemented in ade4, <code>quasieuclid()</code>, <code>lingoes()</code>,
+and <code>cailliez()</code>. The correction of these distances should not adversely
+affect the outcome of the analysis.
+    <h3>On Filtering:</h3>
  Filtering multilocus genotypes is performed by
-  <code><a href='mlg.filter.html'>mlg.filter</a></code>. This can necessarily only be done AMOVA tests 
-  that do not account for within-individual variance. The distance matrix used
-  to calculate the amova is derived from using <code><a href='mlg.filter.html'>mlg.filter</a></code> with
-  the option <code>stats = "distance"</code>, which reports the distance between 
-  multilocus genotype clusters. One useful way to utilize this feature is to
-  correct for genotypes that have equivalent distance due to missing data. 
-  (See example below.)
-    <p></p><h3>On Methods:</h3>
- Both <span class="pkg">ade4</span> and <span class="pkg">pegas</span> have 
-  implementations of AMOVA, both of which are appropriately called "amova". 
-  The ade4 version is faster, but there have been questions raised as to the 
-  validity of the code utilized. The pegas version is slower, but careful 
-  measures have been implemented as to the accuracy of the method. It must be
-  noted that there appears to be a bug regarding permuting analyses where 
-  within individual variance is accounted for (<code>within = TRUE</code>) in the 
-  pegas implementation. If you want to perform permutation analyses on the 
-  pegas implementation, you must set <code>within = FALSE</code>. In addition,
-  while clone correction is implemented for both methods, filtering is only
-  implemented for the ade4 version.
-    
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
-    <p>The ade4 function <code><a href='http://www.rdocumentation.org/packages/ade4/topics/randtest.amova'>randtest.amova</a></code> contains a slight 
-  bug as of version 1.7.4 which causes the wrong alternative hypothesis to be
-  applied on every 4th heirarchical level. Luckily, there is a way to fix it
-  by re-converting the results with the function
-  <code><a href='http://www.rdocumentation.org/packages/ade4/topics/krandtest'>as.krandtest</a></code>. See examples for details.</p>
+<code><a href='mlg.filter.html'>mlg.filter()</a></code>. This can necessarily only be done AMOVA tests that do not
+account for within-individual variance. The distance matrix used to
+calculate the amova is derived from using <code><a href='mlg.filter.html'>mlg.filter()</a></code> with the option
+<code>stats = "distance"</code>, which reports the distance between multilocus
+genotype clusters. One useful way to utilize this feature is to correct for
+genotypes that have equivalent distance due to missing data. (See example
+below.)
+    <h3>On Methods:</h3>
+ Both <span class="pkg">ade4</span> and <span class="pkg">pegas</span> have
+implementations of AMOVA, both of which are appropriately called "amova".
+The ade4 version is faster, but there have been questions raised as to the
+validity of the code utilized. The pegas version is slower, but careful
+measures have been implemented as to the accuracy of the method. It must be
+noted that there appears to be a bug regarding permuting analyses where
+within individual variance is accounted for (<code>within = TRUE</code>) in the pegas
+implementation. If you want to perform permutation analyses on the pegas
+implementation, you must set <code>within = FALSE</code>. In addition, while clone
+correction is implemented for both methods, filtering is only implemented
+for the ade4 version.
+    <h3>On Polyploids:</h3>
+ As of <span class="pkg">poppr</span> version 2.7.0, this
+function is able to calculate phi statistics for within-individual variance
+for polyploid data with <strong>full dosage information</strong>. When a data set does
+not contain full dosage information for all samples, then the resulting
+pseudo-haplotypes will contain missing data, which would result in an
+incorrect estimate of variance.
+    Instead, the AMOVA will be performed on the distance matrix derived from
+allele counts or allele frequencies, depending on the <code>freq</code> option. This
+has been shown to be robust to estimates with mixed ploidy (Ronfort et al.
+1998; Meirmans and Liu 2018). If you wish to brute-force your way to
+estimating AMOVA using missing values, you can split your haplotypes with
+the <code><a href='make_haplotypes.html'>make_haplotypes()</a></code> function.
+    One strategy for addressing ambiguous dosage in your polyploid data set
+would be to convert your data to <span class="pkg">polysat</span>'s <code>genambig</code> class with the
+<code><a href='coercion-methods.html'>as.genambig()</a></code>, estimate allele frequencies with <code><a href='http://www.rdocumentation.org/packages/polysat/topics/deSilvaFreq'>polysat::deSilvaFreq()</a></code>,
+and use these frequencies to randomly sample alleles to fill in the
+ambiguous alleles.
     
     <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
 
@@ -302,12 +316,17 @@ <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>R
 molecular variance inferred from metric distances among DNA haplotypes:
 application to human mitochondrial DNA restriction data. <em>Genetics</em>,
 <strong>131</strong>, 479-491.</p>
+<p>Ronfort, J., Jenczewski, E., Bataillon, T., and Rousset, F. (1998). Analysis
+of population structure in autotetraploid species. <em>Genetics</em>, <strong>150</strong>,
+921–930.</p>
+<p>Meirmans, P., Liu, S. (2018) Analysis of Molecular Variance (AMOVA) for
+Autopolyploids <em>Submitted</em>.</p>
     
     <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
 
-    <p><code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>amova</a></code> (ade4) <code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>amova</a></code> (pegas) 
-  <code><a href='clonecorrect.html'>clonecorrect</a></code> <code><a href='diss.dist.html'>diss.dist</a></code> <code><a href='missingno.html'>missingno</a></code> 
-  <code><a href='http://www.rdocumentation.org/packages/ade4/topics/is.euclid'>is.euclid</a></code> <code>strata</code></p>
+    <p><code><a href='http://www.rdocumentation.org/packages/ade4/topics/amova'>ade4::amova()</a></code>, <code><a href='http://www.rdocumentation.org/packages/pegas/topics/amova'>pegas::amova()</a></code>, <code><a href='clonecorrect.html'>clonecorrect()</a></code>, <code><a href='diss.dist.html'>diss.dist()</a></code>,
+<code><a href='missingno.html'>missingno()</a></code>, <code><a href='http://www.rdocumentation.org/packages/ade4/topics/is.euclid'>ade4::is.euclid()</a></code>, <code>strata()</code>, <code><a href='make_haplotypes.html'>make_haplotypes()</a></code>,
+<code><a href='coercion-methods.html'>as.genambig()</a></code></p>
     
 
     <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
@@ -350,7 +369,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 #&gt; Phi-samples-Pop   0.2803128
 #&gt; Phi-Pop-total     0.7000679
 #&gt; </div><div class='input'><span class='no'>amova.test</span> <span class='kw'>&lt;-</span> <span class='fu'>randtest</span>(<span class='no'>amova.result</span>) <span class='co'># Test for significance</span>
-<span class='fu'>plot</span>(<span class='no'>amova.test</span>)</div><div class='img'><img src='poppr.amova-3.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='no'>amova.test</span></div><div class='output co'>#&gt; class: krandtest lightkrandtest 
+<span class='fu'>plot</span>(<span class='no'>amova.test</span>)</div><div class='img'><img src='poppr.amova-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'><span class='no'>amova.test</span></div><div class='output co'>#&gt; class: krandtest lightkrandtest 
 #&gt; Monte-Carlo tests
 #&gt; Call: randtest.amova(xtest = amova.result)
 #&gt; 
@@ -383,13 +402,6 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='fu'>poppr.amova</span>(<span class='no'>monpop</span>, ~<span class='no'>Symptom</span>/<span class='no'>Year</span>) <span class='co'># gets a warning of zero distances</span>
 <span class='fu'>poppr.amova</span>(<span class='no'>monpop</span>, ~<span class='no'>Symptom</span>/<span class='no'>Year</span>, <span class='kw'>filter</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>threshold</span> <span class='kw'>=</span> <span class='fl'>0.1</span>) <span class='co'># no warning</span>
 
-<span class='co'># Correcting incorrect alternate hypotheses with &gt;2 heirarchical levels</span>
-<span class='co'># </span>
-<span class='no'>mon.amova</span> <span class='kw'>&lt;-</span> <span class='fu'>poppr.amova</span>(<span class='no'>monpop</span>, ~<span class='no'>Symptom</span>/<span class='no'>Year</span>/<span class='no'>Tree</span>)
-<span class='no'>mon.test</span>  <span class='kw'>&lt;-</span> <span class='fu'>randtest</span>(<span class='no'>mon.amova</span>)
-<span class='no'>mon.test</span> <span class='co'># Note alter is less, greater, greater, less</span>
-<span class='no'>alt</span> <span class='kw'>&lt;-</span> <span class='fu'>c</span>(<span class='st'>"less"</span>, <span class='st'>"greater"</span>, <span class='st'>"greater"</span>, <span class='st'>"greater"</span>) <span class='co'># extend this to the number of levels</span>
-<span class='fu'>with</span>(<span class='no'>mon.test</span>, <span class='fu'>as.krandtest</span>(<span class='no'>sim</span>, <span class='no'>obs</span>, <span class='kw'>alter</span> <span class='kw'>=</span> <span class='no'>alt</span>, <span class='kw'>call</span> <span class='kw'>=</span> <span class='no'>call</span>, <span class='kw'>names</span> <span class='kw'>=</span> <span class='no'>names</span>))
 
 <span class='co'># }</span></pre>
   </div>
@@ -402,8 +414,6 @@ <h2>Contents</h2>
 
       <li><a href="#details">Details</a></li>
 
-      <li><a href="#note">Note</a></li>
-
       <li><a href="#references">References</a></li>
 
       <li><a href="#see-also">See also</a></li>
diff --git a/docs/reference/poppr.msn-1.png b/docs/reference/poppr.msn-1.png
index fe285902..13536646 100644
Binary files a/docs/reference/poppr.msn-1.png and b/docs/reference/poppr.msn-1.png differ
diff --git a/docs/reference/poppr.msn.html b/docs/reference/poppr.msn.html
index 627e4484..8d79555a 100644
--- a/docs/reference/poppr.msn.html
+++ b/docs/reference/poppr.msn.html
@@ -288,7 +288,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='no'>A.dist</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='diss.dist.html'>diss.dist</a></span>(<span class='no'>Aeut</span>)
 
 <span class='co'># Graph it.</span>
-<span class='no'>A.msn</span> <span class='kw'>&lt;-</span> <span class='fu'>poppr.msn</span>(<span class='no'>Aeut</span>, <span class='no'>A.dist</span>, <span class='kw'>gadj</span> <span class='kw'>=</span> <span class='fl'>15</span>, <span class='kw'>vertex.label</span> <span class='kw'>=</span> <span class='fl'>NA</span>)</div><div class='img'><img src='poppr.msn-3.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='no'>A.msn</span> <span class='kw'>&lt;-</span> <span class='fu'>poppr.msn</span>(<span class='no'>Aeut</span>, <span class='no'>A.dist</span>, <span class='kw'>gadj</span> <span class='kw'>=</span> <span class='fl'>15</span>, <span class='kw'>vertex.label</span> <span class='kw'>=</span> <span class='fl'>NA</span>)</div><div class='img'><img src='poppr.msn-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 <span class='co'># Find the sizes of the nodes (number of individuals per MLL):</span>
 <span class='kw pkg'>igraph</span><span class='kw ns'>::</span><span class='fu'><a href='http://www.rdocumentation.org/packages/igraph/topics/vertex_attr'>vertex_attr</a></span>(<span class='no'>A.msn</span>$<span class='no'>graph</span>, <span class='st'>"size"</span>)^<span class='fl'>2</span></div><div class='output co'>#&gt;   [1]  2  1  2  2  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  9  1  1  5  1  1
 #&gt;  [26]  2  1  1  1  1  2  3  1  1  2  1  1  1  2  1  1  1  1  1  1  2  1  2  1  1
diff --git a/docs/reference/psex.html b/docs/reference/psex.html
index 6f98664f..ac6a6beb 100644
--- a/docs/reference/psex.html
+++ b/docs/reference/psex.html
@@ -244,7 +244,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 
 <span class='co'># With multiple encounters</span>
 <span class='no'>Pram_psex</span> <span class='kw'>&lt;-</span> <span class='fu'>psex</span>(<span class='no'>Pram</span>, <span class='kw'>by_pop</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"multiple"</span>)
-<span class='fu'>plot</span>(<span class='no'>Pram_psex</span>, <span class='kw'>log</span> <span class='kw'>=</span> <span class='st'>"y"</span>, <span class='kw'>col</span> <span class='kw'>=</span> <span class='fu'>ifelse</span>(<span class='no'>Pram_psex</span> <span class='kw'>&gt;</span> <span class='fl'>0.05</span>, <span class='st'>"red"</span>, <span class='st'>"blue"</span>))</div><div class='input'><span class='fu'>abline</span>(<span class='kw'>h</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>lty</span> <span class='kw'>=</span> <span class='fl'>2</span>)</div><div class='input'><span class='fu'>title</span>(<span class='st'>"Probability of multiple encounters"</span>)</div><div class='img'><img src='psex-3.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
+<span class='fu'>plot</span>(<span class='no'>Pram_psex</span>, <span class='kw'>log</span> <span class='kw'>=</span> <span class='st'>"y"</span>, <span class='kw'>col</span> <span class='kw'>=</span> <span class='fu'>ifelse</span>(<span class='no'>Pram_psex</span> <span class='kw'>&gt;</span> <span class='fl'>0.05</span>, <span class='st'>"red"</span>, <span class='st'>"blue"</span>))</div><div class='input'><span class='fu'>abline</span>(<span class='kw'>h</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>lty</span> <span class='kw'>=</span> <span class='fl'>2</span>)</div><div class='input'><span class='fu'>title</span>(<span class='st'>"Probability of multiple encounters"</span>)</div><div class='img'><img src='psex-1.png' alt='' width='700' height='432.632880098887' /></div><span class='co'># NOT RUN {</span>
 <span class='co'># For a single encounter (default)</span>
 <span class='no'>Pram_psex</span> <span class='kw'>&lt;-</span> <span class='fu'>psex</span>(<span class='no'>Pram</span>, <span class='kw'>by_pop</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
 <span class='fu'>plot</span>(<span class='no'>Pram_psex</span>, <span class='kw'>log</span> <span class='kw'>=</span> <span class='st'>"y"</span>, <span class='kw'>col</span> <span class='kw'>=</span> <span class='fu'>ifelse</span>(<span class='no'>Pram_psex</span> <span class='kw'>&gt;</span> <span class='fl'>0.05</span>, <span class='st'>"red"</span>, <span class='st'>"blue"</span>))
diff --git a/docs/reference/samp.ia.html b/docs/reference/samp.ia.html
index 9888e076..feae2556 100644
--- a/docs/reference/samp.ia.html
+++ b/docs/reference/samp.ia.html
@@ -186,12 +186,12 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
            <span class='kw'>n.snp.struc</span> <span class='kw'>=</span> <span class='fl'>5e2</span>, <span class='kw'>ploidy</span> <span class='kw'>=</span> <span class='fl'>2</span>,
            <span class='kw'>parallel</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
 <span class='fu'>position</span>(<span class='no'>x</span>) <span class='kw'>&lt;-</span> <span class='fu'>sort</span>(<span class='fu'>sample</span>(<span class='fl'>1e4</span>, <span class='fl'>1e3</span>))
-<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>samp.ia</span>(<span class='no'>x</span>)</div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='input'><span class='fu'>hist</span>(<span class='no'>res</span>, <span class='kw'>breaks</span> <span class='kw'>=</span> <span class='st'>"fd"</span>)</div><div class='img'><img src='samp.ia-5.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>samp.ia</span>(<span class='no'>x</span>)</div><div class='output co'>#&gt; 
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 <span class='co'># with unstructured snps assuming 1e4 positions</span>
 <span class='fu'>set.seed</span>(<span class='fl'>999</span>)
 <span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>glSim</span>(<span class='kw'>n.ind</span> <span class='kw'>=</span> <span class='fl'>10</span>, <span class='kw'>n.snp.nonstruc</span> <span class='kw'>=</span> <span class='fl'>1e3</span>, <span class='kw'>ploidy</span> <span class='kw'>=</span> <span class='fl'>2</span>)
 <span class='fu'>position</span>(<span class='no'>x</span>) <span class='kw'>&lt;-</span> <span class='fu'>sort</span>(<span class='fu'>sample</span>(<span class='fl'>1e4</span>, <span class='fl'>1e3</span>))
-<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>samp.ia</span>(<span class='no'>x</span>)</div><div class='output co'>#&gt; 
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+<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>samp.ia</span>(<span class='no'>x</span>)</div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='input'><span class='fu'>hist</span>(<span class='no'>res</span>, <span class='kw'>breaks</span> <span class='kw'>=</span> <span class='st'>"fd"</span>)</div><div class='img'><img src='samp.ia-2.png' alt='' width='700' height='432.632880098887' /></div></pre>
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
     <h2>Contents</h2>
diff --git a/docs/reference/win.ia.html b/docs/reference/win.ia.html
index f8460226..15b9cf84 100644
--- a/docs/reference/win.ia.html
+++ b/docs/reference/win.ia.html
@@ -174,7 +174,7 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examp
 <span class='fu'>set.seed</span>(<span class='fl'>999</span>)
 <span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>glSim</span>(<span class='kw'>n.ind</span> <span class='kw'>=</span> <span class='fl'>10</span>, <span class='kw'>n.snp.nonstruc</span> <span class='kw'>=</span> <span class='fl'>5e2</span>, <span class='kw'>n.snp.struc</span> <span class='kw'>=</span> <span class='fl'>5e2</span>, <span class='kw'>ploidy</span> <span class='kw'>=</span> <span class='fl'>2</span>)
 <span class='fu'>position</span>(<span class='no'>x</span>) <span class='kw'>&lt;-</span> <span class='fu'>sort</span>(<span class='fu'>sample</span>(<span class='fl'>1e4</span>, <span class='fl'>1e3</span>))
-<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>win.ia</span>(<span class='no'>x</span>, <span class='kw'>window</span> <span class='kw'>=</span> <span class='fl'>300L</span>) <span class='co'># Calculate for windows of size 300</span></div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='input'><span class='fu'>plot</span>(<span class='no'>res</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"l"</span>)</div><div class='img'><img src='win.ia-3.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
+<span class='no'>res</span> <span class='kw'>&lt;-</span> <span class='fu'>win.ia</span>(<span class='no'>x</span>, <span class='kw'>window</span> <span class='kw'>=</span> <span class='fl'>300L</span>) <span class='co'># Calculate for windows of size 300</span></div><div class='output co'>#&gt; 
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  |======================================================================| 100%</div><div class='input'><span class='fu'>plot</span>(<span class='no'>res</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"l"</span>)</div><div class='img'><img src='win.ia-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'>
 </div><span class='co'># NOT RUN {</span>
 <span class='co'># unstructured snps</span>
 <span class='fu'>set.seed</span>(<span class='fl'>999</span>)