<p>My lab has started using the <a href='http://www.halogenomics.com/haloplex/how-it-works'>Haloplex technology</a> to capture the regions of interest.</p>

<p>With this technology most of the reads have the same start/end (I've found that removing the duplicates would reduce the coverage to ~1 base). The reads are grouped in a vertical 'cluster' that can contains more than 1000 reads.</p>

<p><img src='http://i.imgur.com/nW6Le.jpg' alt='enter image description here' /></p>

<p>Have you ever used this technology ? I'm currently using <a href='http://samtools.sourceforge.net/'>samtools</a> mpileup with the  option 
<strong>"-A"</strong> ( count anomalous read pairs) and <strong>"-d 8000"</strong> ( max per-BAM depth).</p>

<p>I'm afraid there is a kind of bias with haloplex: is it safe to use <a href='http://samtools.sourceforge.net/'>samtools</a> or Gatk to call the variants ? </p>

<p>Pierre</p>

<p>In general, any capture-based technology will have bias.  In your case, you're worried that the the bias will be amplified in the detection step.</p>

<p>I would use as many methods as possible to call these alleles, and see what the differences are.  With coverage this high, there should be little variation in results.</p>

<p>Furthermore, simulation could provide an avenue to assessing potential bias in the case of haploplex resequencing.  In simulated tests, I have observed that samtools and GATK have lower sensitivity than our caller (freebayes) at high depths, but all perform roughly the same at lower coverage.  It's not entirely clear to me why this is, but I suspect default parameter selection may play a role.  I haven't evaluated other callers, and it's possible that others may perform even better in high-depth contexts.</p>
