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vcf2genlight.html
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<h1 class="title toc-ignore">vcf2genlight</h1>
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<p>Different R packages have created different data structures to hold your data when it is imported into R. This is analagous to the different file formats you may have used to analyze your data in software outside of R. We’ve tried to engineer a suite of functions to convert data structures among the various R packages we typically use. The R package adegenet is a popular R package used for population genetic analysis and it works on data structures called ‘genlight’ objects. Here we use the function <code>vcfR2genlight()</code> to convert our vcfR object to a genlight object. This makes our VCF data available to the analyses in adegenet.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1"></a>x <-<span class="st"> </span><span class="kw">vcfR2genlight</span>(vcf)</span></code></pre></div>
<pre><code>## Warning in vcfR2genlight(vcf): Found 44 loci with more than two alleles.
## Objects of class genlight only support loci with two alleles.
## 44 loci will be omitted from the genlight object.</code></pre>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1"></a>x</span></code></pre></div>
<pre><code>## /// GENLIGHT OBJECT /////////
##
## // 18 genotypes, 2,146 binary SNPs, size: 240.4 Kb
## 0 (0 %) missing data
##
## // Basic content
## @gen: list of 18 SNPbin
##
## // Optional content
## @ind.names: 18 individual labels
## @loc.names: 2146 locus labels
## @chromosome: factor storing chromosomes of the SNPs
## @position: integer storing positions of the SNPs
## @other: a list containing: elements without names</code></pre>
<p>A genlight object only supports biallelic, or binary, variants. That is, variants with no more than two alleles. However, variant call format data can include multiple alleles. When we created our genlight object we recieved a warning message indicating that our vcfR object had variants with more than two alleles and that it was being subset to only biallelic variants. This is one of several important differences in how data is handled in VCF data versus genlight objects.</p>
<p>Another important difference among VCF and genlight data is how the genotypes are stored. In VCF data the alleles are delimited by either a pipe or a forward slash (‘|’, ‘/’ respectively). Because genlight objects only use biallelic loci the genotypes can be recoded as 0, 1 and 2. These correspond to homozygous for the reference or zero allele, heterozygote or homozygous for the first alternate allele. We can validate this by checking a few select genotypes from both the vcfR object and the genlight object.</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1"></a><span class="co"># vcfR</span></span>
<span id="cb5-2"><a href="#cb5-2"></a>gt <-<span class="st"> </span><span class="kw">extract.gt</span>(vcf, <span class="dt">element =</span> <span class="st">"GT"</span>)</span>
<span id="cb5-3"><a href="#cb5-3"></a>gt[<span class="kw">c</span>(<span class="dv">2</span>,<span class="dv">6</span>,<span class="dv">18</span>), <span class="dv">1</span><span class="op">:</span><span class="dv">3</span>]</span></code></pre></div>
<pre><code>## BL2009P4_us23 DDR7602 IN2009T1_us22
## Supercontig_1.50_80063 "1|0" "1|0" "0|1"
## Supercontig_1.50_80089 "0|0" "1|0" "0|1"
## Supercontig_1.50_94108 "0|1" "0|1" "1|1"</code></pre>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1"></a><span class="co"># genlight</span></span>
<span id="cb7-2"><a href="#cb7-2"></a><span class="kw">t</span>(<span class="kw">as.matrix</span>(x))[<span class="kw">c</span>(<span class="dv">1</span>,<span class="dv">5</span>,<span class="dv">17</span>), <span class="dv">1</span><span class="op">:</span><span class="dv">3</span>]</span></code></pre></div>
<pre><code>## BL2009P4_us23 DDR7602 IN2009T1_us22
## Supercontig_1.50_80063 1 1 1
## Supercontig_1.50_80089 0 1 1
## Supercontig_1.50_94108 1 1 2</code></pre>
<p>Note that in VCF data the samples are in columns and the variants are in rows. In genlight objects, and many other R objects, the samples are in rows while the variants are in columns. We can use the transpose function (<code>t()</code>) to convert between these two states.</p>
<p>Yet another difference among VCF data and genlight objects is that in VCF data there is no concept of ‘population.’ The package adegenet was designed specifically for the analysis of population data, so its genlight object has a place (a ‘slot’) to hold this information. Because there is no population data in VCF data, if we want population data we’ll have to set it ourselves.</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1"></a><span class="kw">library</span>(adegenet)</span>
<span id="cb9-2"><a href="#cb9-2"></a><span class="kw">pop</span>(x) <-<span class="st"> </span><span class="kw">as.factor</span>(<span class="kw">c</span>(<span class="st">"us"</span>, <span class="st">"eu"</span>, <span class="st">"us"</span>, <span class="st">"af"</span>, <span class="st">"eu"</span>, <span class="st">"us"</span>, <span class="st">"mx"</span>, <span class="st">"eu"</span>, <span class="st">"eu"</span>, <span class="st">"sa"</span>, <span class="st">"mx"</span>, <span class="st">"sa"</span>, <span class="st">"us"</span>, <span class="st">"sa"</span>, <span class="st">"Pmir"</span>, <span class="st">"us"</span>, <span class="st">"eu"</span>, <span class="st">"eu"</span>))</span>
<span id="cb9-3"><a href="#cb9-3"></a><span class="kw">popNames</span>(x)</span></code></pre></div>
<pre><code>## [1] "af" "eu" "mx" "Pmir" "sa" "us"</code></pre>
<p>Our population designation consists of a vector, that is the same length as the number of samples we have, where each element indicates which population each sample belongs to. By using the <code>as.factor()</code> function we transform the “vector” into a “factor”. A factor understands that all of the elements that are named “us” or “eu” are all part of the same group. This is why when we ask for the <code>popNames</code> we get a vector where each population is represented only once.</p>
<p>Yet another difference among VCF data and genlight objects is the concept of ploidy. In VCF data each variant is treated independently. This means that in theory VCF data may contain data that is of mixed ploidy. In a genlight object different samples may be of different ploidy levels, but within each sample all of its loci must be of the same ploidy level. Here we’ll set the ploidy of all the samples in the genlight object to the same ploidy.</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1"></a><span class="kw">ploidy</span>(x) <-<span class="st"> </span><span class="dv">2</span></span></code></pre></div>
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