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<title>Interaction between phylogenetic uncertainty and sensitivity to species sampling - Phylogenetic Linear Regression — tree_samp_phylm • sensiPhy</title>


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species and detecting the effects on parameter estimates in a phylogenetic
linear regression, while evaluating uncertainty in trees topology." />
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    <h1>Interaction between phylogenetic uncertainty and sensitivity to species sampling - Phylogenetic Linear Regression</h1>
    <small class="dont-index">Source: <a href='https://github.com/paternogbc/sensiPhy/blob/master/R/tree_samp_phylm.R'><code>R/tree_samp_phylm.R</code></a></small>
    <div class="hidden name"><code>tree_samp_phylm.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Performs analyses of sensitivity to species sampling by randomly removing
species and detecting the effects on parameter estimates in a phylogenetic
linear regression, while evaluating uncertainty in trees topology.</p>
    </div>

    <pre class="usage"><span class='fu'>tree_samp_phylm</span>(
  <span class='no'>formula</span>,
  <span class='no'>data</span>,
  <span class='no'>phy</span>,
  <span class='kw'>n.sim</span> <span class='kw'>=</span> <span class='fl'>30</span>,
  <span class='kw'>n.tree</span> <span class='kw'>=</span> <span class='fl'>2</span>,
  <span class='kw'>breaks</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>0.1</span>, <span class='fl'>0.5</span>, <span class='fl'>0.1</span>),
  <span class='kw'>model</span> <span class='kw'>=</span> <span class='st'>"lambda"</span>,
  <span class='kw'>track</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
  <span class='no'>...</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>formula</th>
      <td><p>The model formula</p></td>
    </tr>
    <tr>
      <th>data</th>
      <td><p>Data frame containing species traits with row names matching tips
in <code>phy</code>.</p></td>
    </tr>
    <tr>
      <th>phy</th>
      <td><p>A phylogeny (class 'phylo') matching <code>data</code>.</p></td>
    </tr>
    <tr>
      <th>n.sim</th>
      <td><p>The number of times species are randomly deleted for each
<code>break</code>.</p></td>
    </tr>
    <tr>
      <th>n.tree</th>
      <td><p>Number of times to repeat the analysis with n different trees picked 
randomly in the multiPhylo file.</p></td>
    </tr>
    <tr>
      <th>breaks</th>
      <td><p>A vector containing the percentages of species to remove.</p></td>
    </tr>
    <tr>
      <th>model</th>
      <td><p>The phylogenetic model to use (see Details). Default is <code>lambda</code>.</p></td>
    </tr>
    <tr>
      <th>track</th>
      <td><p>Print a report tracking function progress (default = TRUE)</p></td>
    </tr>
    <tr>
      <th>...</th>
      <td><p>Further arguments to be passed to <code>phylolm</code></p></td>
    </tr>
    </table>

    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>

    <p>The function <code>samp_phylm</code> returns a list with the following
components:</p>
<p><code>formula</code>: The formula</p>
<p><code>full.model.estimates</code>: Coefficients, aic and the optimised
value of the phylogenetic parameter (e.g. <code>lambda</code> or <code>kappa</code>) for
the full model without deleted species.</p>
<p><code>sensi.estimates</code>: A data frame with all simulation
estimates. Each row represents a model rerun with a given number of species
<code>n.remov</code> removed, representing <code>n.percent</code> of the full dataset.
Columns report the calculated regression intercept (<code>intercept</code>),
difference between simulation intercept and full model intercept (<code>DIFintercept</code>),
the percentage of change in intercept compared to the full model (<code>intercept.perc</code>)
and intercept p-value (<code>pval.intercept</code>). All these parameters are also reported
for the regression slope (<code>DIFestimate</code> etc.). Additionally, model aic value
(<code>AIC</code>) and the optimised value (<code>optpar</code>) of the phylogenetic
parameter (e.g. <code>kappa</code> or <code>lambda</code>, depending on the phylogenetic model
used) are reported. Lastly we reported the standardised difference in intercept 
(<code>sDIFintercept</code>) and slope (<code>sDIFestimate</code>).</p>
<p><code>sign.analysis</code> For each break (i.e. each percentage of species
removed) this reports the percentage of statistically significant (at p&lt;0.05)
intercepts (<code>perc.sign.intercept</code>) over all repetitions as well as the
percentage of statisticaly significant (at p&lt;0.05) slopes (<code>perc.sign.estimate</code>).</p>
<p><code>data</code>: Original full dataset.
#' @note Please be aware that dropping species may reduce power to detect 
significant slopes/intercepts and may partially be responsible for a potential 
effect of species removal on p-values. Please also consult standardised differences
in the (summary) output.</p>
    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>

    <p>This function randomly removes a given percentage of species (controlled by
<code>breaks</code>) from the full phylogenetic linear regression, fits a phylogenetic
linear regression model without these species using <code><a href='https://rdrr.io/pkg/phylolm/man/phylolm.html'>phylolm</a></code>,
repeats this many times (controlled by <code>n.sim</code>), stores the results and
calculates the effects on model parameters. It repeats this operation using n trees, 
randomly picked in a multiPhylo file.</p>
<p>All phylogenetic models from <code>phylolm</code> can be used, i.e. <code>BM</code>,
<code>OUfixedRoot</code>, <code>OUrandomRoot</code>, <code>lambda</code>, <code>kappa</code>,
<code>delta</code>, <code>EB</code> and <code>trend</code>. See ?<code>phylolm</code> for details.</p>
<p>Currently, this function can only implement simple linear models (i.e. \(trait~
predictor\)). In the future we will implement more complex models.</p>
<p>Output can be visualised using <code>sensi_plot</code>.</p>
    <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>

    <p>Paterno, G. B., Penone, C. Werner, G. D. A. 
<a href='http://doi.wiley.com/10.1111/2041-210X.12990'>sensiPhy: 
An r-package for sensitivity analysis in phylogenetic 
comparative methods.</a> Methods in Ecology and Evolution 
2018, 9(6):1461-1467</p>
<p>Werner, G.D.A., Cornwell, W.K., Sprent, J.I., Kattge, J. &amp; Kiers, E.T. (2014).
A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation
in angiosperms. Nature Communications, 5, 4087.</p>  
<p>Ho, L. S. T. and Ane, C. 2014. "A linear-time algorithm for 
Gaussian and non-Gaussian trait evolution models". Systematic Biology 63(3):397-408.</p>
    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>

    <div class='dont-index'><p><code><a href='https://rdrr.io/pkg/phylolm/man/phylolm.html'>phylolm</a></code>, <code><a href='samp_phylm.html'>samp_phylm</a></code>,
<code><a href='tree_phylm.html'>tree_phylm</a></code>,<code><a href='tree_samp_phyglm.html'>tree_samp_phyglm</a></code>,<code><a href='sensi_plot.html'>sensi_plot</a></code></p></div>

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># Load data:</span>
<span class='fu'><a href='https://rdrr.io/r/utils/data.html'>data</a></span>(<span class='no'>alien</span>)
<span class='co'># Run analysis:</span>
<span class='no'>samp</span> <span class='kw'>&lt;-</span> <span class='fu'>tree_samp_phylm</span>(<span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span>(<span class='no'>gestaLen</span>) ~ <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span>(<span class='no'>adultMass</span>), <span class='kw'>phy</span> <span class='kw'>=</span> <span class='no'>alien</span>$<span class='no'>phy</span>,
                                    <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>alien</span>$<span class='no'>data</span>, <span class='kw'>n.tree</span> <span class='kw'>=</span> <span class='fl'>5</span>, <span class='kw'>n.sim</span><span class='kw'>=</span><span class='fl'>10</span>)
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>samp</span>)
<span class='fu'><a href='https://rdrr.io/r/utils/head.html'>head</a></span>(<span class='no'>samp</span>$<span class='no'>sensi.estimates</span>)
<span class='co'># Visual diagnostics</span>
<span class='fu'><a href='sensi_plot.html'>sensi_plot</a></span>(<span class='no'>samp</span>)
<span class='fu'><a href='sensi_plot.html'>sensi_plot</a></span>(<span class='no'>samp</span>, <span class='kw'>graphs</span> <span class='kw'>=</span> <span class='fl'>1</span>)
<span class='fu'><a href='sensi_plot.html'>sensi_plot</a></span>(<span class='no'>samp</span>, <span class='kw'>graphs</span> <span class='kw'>=</span> <span class='fl'>2</span>)
}
<span class='co'># \dontshow{</span>
<span class='co'># Load data:</span>
<span class='fu'><a href='https://rdrr.io/r/utils/data.html'>data</a></span>(<span class='no'>alien</span>)
<span class='co'># Run analysis:</span>
<span class='no'>samp</span> <span class='kw'>&lt;-</span> <span class='fu'>tree_samp_phylm</span>(<span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span>(<span class='no'>gestaLen</span>) ~ <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span>(<span class='no'>adultMass</span>), <span class='kw'>phy</span> <span class='kw'>=</span> <span class='no'>alien</span>$<span class='no'>phy</span>,
                                    <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>alien</span>$<span class='no'>data</span>, <span class='kw'>n.tree</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>n.sim</span><span class='kw'>=</span><span class='fl'>1</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: NA's in response or predictor, rows with NA's were removed</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Some phylo tips do not match species in data (this can be due to NA removal) species were dropped from phylogeny or data</span></div><div class='output co'>#&gt; <span class='message'>Used dataset has  84  species that match data and phylogeny</span></div><div class='output co'>#&gt; 
  |                                                                            
  |                                                                      |   0%
  |                                                                            
  |======================================================================| 100%</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>samp</span>)</div><div class='output co'>#&gt; <span class='message'>5 simulations saved, see output$sensi.estimates to acess all simulations</span></div><div class='output co'>#&gt;   % Species Removed % Significant Intercepts Mean Intercept Change (%)
#&gt; 1                10                      100                       1.7
#&gt; 2                20                      100                       3.3
#&gt; 3                30                      100                       0.9
#&gt; 4                40                      100                       2.5
#&gt; 5                50                      100                       3.4
#&gt;   Mean sDIFintercept % Significant Estimates Mean Estimate Change (%)
#&gt; 1         -0.6002325                     100                      3.4
#&gt; 2          1.1585638                     100                      6.1
#&gt; 3         -0.3100876                     100                      8.2
#&gt; 4          0.8701820                     100                     16.5
#&gt; 5         -1.2022838                     100                      7.5
#&gt;   Mean sDIFestimate
#&gt; 1         0.4131880
#&gt; 2        -0.7436704
#&gt; 3         1.0016718
#&gt; 4         2.0032507
#&gt; 5         0.9136294</div><div class='input'><span class='co'># Visual diagnostics</span>
<span class='fu'><a href='sensi_plot.html'>sensi_plot</a></span>(<span class='no'>samp</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: `fun.y` is deprecated. Use `fun` instead.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: `fun.y` is deprecated. Use `fun` instead.</span></div><div class='output co'>#&gt; <span class='warning'>Warning: `fun.y` is deprecated. Use `fun` instead.</span></div><div class='img'><img src='tree_samp_phylm-1.png' alt='' width='700' height='433' /></div><div class='input'># }
</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="#references">References</a></li>
      <li><a href="#see-also">See also</a></li>
      <li><a href="#examples">Examples</a></li>
    </ul>

    <h2>Author</h2>
    <p>Gustavo Paterno, Gijsbert D.A. Werner &amp; Caterina Penone</p>
  </div>
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