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(This article was first published on <strong><a href="http://moderndata.plot.ly/interactive-qq-plots-r-plotly/"> R – Modern Data</a></strong>, and kindly contributed to <a rel="nofollow" href="http://www.r-bloggers.com/">R-bloggers)</a> </div>
<h3>Introduction</h3>
<p>In a recent <a target="_blank" href="http://moderndata.plot.ly/manhattanly-r-package-for-interactive-manhattan-plots/">blog post</a>, I introduced the new R package, <a target="_blank" href="https://cran.r-project.org/web/packages/manhattanly/">manhattanly</a>, which creates interactive manhattan plots using the <a target="_blank" href="https://plot.ly/">plotly.js</a> engine. </p>
<p>In this post, I describe how to create interactive Q-Q plots using the <a target="_blank" href="https://cran.r-project.org/web/packages/manhattanly/">manhattanly</a> package. Q-Q plots tell us about the distributional assumptions of the observed test statistics and are common visualisation tools in statistical analyses.</p>
<p>Visit the <a target="_blank" href="https://github.com/sahirbhatnagar/manhattanly">package website</a> for full details and example usage. </p>
<h3>Quick Start</h3>
<p>The following three lines of code will produce the Q-Q plot below</p>

<pre>install.packages(&quot;manhattanly&quot;)
library(manhattanly)
qqly(HapMap, snp = &quot;SNP&quot;, gene = &quot;GENE&quot;)</pre>

<p><iframe height="800" width="900" src="https://plot.ly/~sahirbhatnagar/54.embed"></iframe></p>
<p>Notice that we have added two annotations (the SNP and nearest GENE), that are revealed when hovering the mouse over a point. This feature of interactive Q-Q plots adds a great deal of information to the plot without cluttering it with text. </p>
<h3>The Data</h3>
<p>Inspired by the <a target="_blank" href="https://cran.r-project.org/web/packages/heatmaply/vignettes/heatmaply.html">heatmaply</a> package by <a target="_blank" href="http://www.r-statistics.com/">Tal Galili</a>, we split the tasks into data pre-processing and plot rendering. Therefore, we can use the <code>manhattanly::qqr</code> function to get the data used to produce a Q-Q plot. This allows flexibility in the rendering of the plot, since any graphics package, such as <code>plot</code> in base R can make used to create the plot.</p>
<p>The plot data is derived using the <code>manhattanly::qqr</code> function:</p>

<pre>qqrObject &lt;- qqr(HapMap)
str(qqrObject)</pre>

<p><code><br>
## List of 6<br>
##  $ data           :'data.frame': 14412 obs. of  3 variables:<br>
##   ..$ P       : num [1:14412] 6.75e-10 3.41e-09 3.95e-09 4.71e-09 5.02e-09 ...<br>
##   ..$ OBSERVED: num [1:14412] 9.17 8.47 8.4 8.33 8.3 ...<br>
##   ..$ EXPECTED: num [1:14412] 4.46 3.98 3.76 3.61 3.51 ...<br>
##  $ pName          : chr &quot;P&quot;<br>
##  $ snpName        : logi NA<br>
##  $ geneName       : logi NA<br>
##  $ annotation1Name: logi NA<br>
##  $ annotation2Name: logi NA<br>
##  - attr(*, &quot;class&quot;)= chr &quot;qqr&quot;<br>
</code> </p>

<pre>head(qqrObject[[&quot;data&quot;]])</pre>

<p><code><br>
##                P OBSERVED EXPECTED<br>
## 4346 6.75010e-10 9.170690 4.459754<br>
## 4347 3.41101e-09 8.467117 3.982633<br>
## 4344 3.95101e-09 8.403292 3.760784<br>
## 4338 4.70701e-09 8.327255 3.614656<br>
## 4342 5.02201e-09 8.299122 3.505512<br>
## 4341 6.22801e-09 8.205651 3.418362<br>
</code></p>
<p>This <code>qqrObject</code> which is of class <code>qqr</code> can also be passed to the <code>manhattanly::qqly</code> function to produce the inteactive Q-Q plot above:</p>

<pre>qqly(qqrObject)</pre>

<h3>Related Work</h3>
<p>This work is based on the <a target="_blank" href="https://github.com/stephenturner/qqman">qqman</a> package by <a target="_blank" href="http://stephenturner.us/">Stephen Turner</a>. It produces similar manhattan and Q-Q plots as the <code>qqman::manhattan</code> and <code>qqman::qq</code> functions; the main difference here is being able to interact with the plot, including extra annotation information and seamless integration with HTML.</p>
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