Hi all,

We're performing NGS on cancer DNA samples with a custom panel of target regions in different genes.

From your experience & knowledge, which tools do you recommend using for our purpose:

1. Finding structural variants (SVs) such as inversions, large indels, translocations, tandem duplications, etc.
2. CNV (copy number variantion) discovery for only a **single** sample (many tools I've found were for multiple samples).

If I'm not mistaken I should look for tools that are suitable for exome data rather than whole genome because of our sequencing methods and custom panel.

Thank you very much in advance!

---

I realize this has been somewhat asked before but the posts I've found were at least 2-3 years old and didn't elaborate on cancer genomics or exome sequencing. It was also unclear to me which CNV discovery tools are suitable for single samples. I hope this isn't out of line.
<p>Lumpy, Delly, Manta, and Pindel are good for detecting structural variation and will work on exome/targeted samples. For CNV detection, some recent review articles give an overview of what&#39;s available for your application:</p>

<ul>
	<li>http://bib.oxfordjournals.org/cgi/doi/10.1093/bib/bbu004</li>
	<li>http://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-15-732</li>
</ul>

<p>These articles are not comprehensive. A couple of tools not mentioned there but worth checking out are <a href="http://www.bioconductor.org/packages/release/bioc/html/CopywriteR.html">CopywriteR</a> (Bioconductor) and <a href="http://cnvkit.readthedocs.org/en/latest/">CNVkit</a> (mine; Unix command line) -- these are relevant if you&#39;re using hybrid capture, but less so for targeted amplicon capture. In the latter case, try <a href="https://oncocnv.curie.fr/">OncoCNV</a>.</p>

<p>In general you can get a good list of tools that are worth using by looking at existing validated pipelines like <a href="https://bcbio-nextgen.readthedocs.org/en/latest/">bcbio-nextgen</a> and <a href="https://github.com/hall-lab/speedseq">speedseq</a>. Even if you don&#39;t use these pipelines directly, you can learn from others&#39; experience by reading the documentation they provide.</p>
