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<p>
<center>
<h3>vcfR documentation</h3>
by
<br>
Brian J. Knaus and Niklaus J. Grünwald
</center>
</p>
<div id="header">
<h1 class="title toc-ignore">Subsetting data to a single chromosome</h1>
</div>
<p>The functions in vcfR are designed to work on a single chromosome.
Many genomes don’t actually have chromosomes but instead have
supercontigs or contigs. Here I use the terms chromosome, supercontig
and contig as synonyms. They make for a nice way to subset genomic data
to a smaller unit, and this unit has a convenient coordinant system.
Depending on the organization of your data, you may have to subset some
of your files before you can use them in vcfR. Here I demontrate how I
accomplish this.</p>
<div id="subsetting-a-fasta-file-to-one-chromosome"
class="section level2">
<h2>Subsetting a FASTA file to one chromosome</h2>
<p>A FASTA file for a genome typically consists of many sequences
(chromosomes, supercontigs, contigs, etc.). Typically these can be read
into R and subset within R. We can use the function
<code>read.dna()</code> from the package ‘ape’ to read in our FASTA to
an object of class DNAbin. We can then subset this object to a single
sequence with the function <code>grep()</code> and a regular expression.
More information on these topics can be found within R with
<code>?grep</code> and <code>?"regular expression"</code></p>
<pre class="r"><code>library(ape)
dna <- read.dna("pinf_super_contigs.fa", format = "fasta")
dna2 <- dna[ grep( "Supercontig_1.1 ", names(dna) ) ]
names(dna2) <- "Supercontig_1.1"
dna2 <- as.matrix(dna2)</code></pre>
<p>Using this example (with your FASTA file name and chromosome name)
should result in an object of class DNAbin that consists of a single
sequence. Note that I’ve used the function <code>names()</code> to
rename the sequence. It has been my experience that genomic data files
do not always include a consistent naming convention. This is how I
standardize the names.</p>
</div>
<div id="subsetting-a-gff-file" class="section level2">
<h2>Subsetting a GFF file</h2>
<p>Annotation files can be easily subset as well. A GFF file is simply a
tabular file with the chromosome in the first column. This can also be
subset with a regular expression.</p>
<pre class="r"><code>gff <- read.table('gff_file.gff', sep="\t", quote="")
gff2 <- gff[grep("Supercontig_1.1", gff[,1]),]</code></pre>
</div>
<div id="subsetting-a-vcf-file" class="section level2">
<h2>Subsetting a VCF file</h2>
<p>I personally like to call variants on a per chromosome basis and send
each chromosome as a seperate job to our SGE system. The genome I
currently work on has about 5,000 supercontigs. This means I create
about 5,000 jobs and therefore split the task of variant calling into
many smaller jobs. This results one chromosome per VCF file and means I
do not have to subset my VCF files.</p>
<p>You may have to subset your VCF file. (Okay, I do too sometimes.) I
suggest you do this outside of R because you may not have enough memory
to read the entire file into memory. In a Unix environment this can be
accomplished at the command line.</p>
<pre class="bash"><code>grep "^#" my_variants.vcf > header.vcf # Meta
grep "^Supercontig_1.1" my_variants.vcf > tmp.vcf # Body
cat header.vcf tmp.vcf > sc1.vcf.gz</code></pre>
<p>If you’re working with compressed data it can be handled
similarly.</p>
<pre class="bash"><code>zgrep "^#" my_variants.vcf.gz | gzip -c > header.vcf.gz # Meta
zgrep "^Supercontig_1.1" my_variants.vcf.gz > tmp.vcf.gz # Body
zcat header.vcf.gz tmp.vcf.gz | gzip -c > sc1.vcf.gz</code></pre>
<p>This could also be accomplished with <a
href="https://vcftools.github.io/">VCFtools</a> (which may help Windows
users as well).</p>
</div>
<div id="vcfr" class="section level2">
<h2>vcfR</h2>
<p>You should now be able to import your VCF data with vcfR.</p>
<pre class="r"><code>library(vcfR)
vcf <- read.vcfR("sc1.vcf")
chrom <- create.chromR(name='Supercontig', vcf=vcf, seq=dna2, ann=gff2)</code></pre>
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<p>Copyright © 2017, 2018 Brian J. Knaus. All rights reserved.</p>
<p>USDA Agricultural Research Service, Horticultural Crops Research Lab.</p>
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