amplicon based germline CNV caller

Question

[J.F.Jiang]

Hi all,

We used multiplex PCR to enrich the 2000 target region, including 25 amplicons in CYP2D6. We want to analyze the CNV status of CYP2D6, which can change the dosage of drugs based on metabolizer type.

I am wondering if there is any existing tool that can manage this?

Best, Junfeng

Answer 1

[bernatgel]

I have no direct experience with any of them, but there are a few tools available for that. Some of them talk about targeted sequencing but do not specify if they would work for amplicons or only for hybridization based data. Most of them are designed to work with germinal data, since they are aimed at genetic diagnostics.

• DECoN
• CoNVaNDING
• panelcn.MOPS
• CNVnator
• VisCap
• CONVector

There are many other CNV callers out there, but beware that some of them will only work for WES or WGS with a reasonable "continuity" of the data and so would not work for a 2000 amplicon panel like yours.

[J.F.Jiang]

Thanks,

I've tried severals of them already, but none works fine based on my PCR-based data.

Answer 2

[Eric T.]

OncoCNV is designed for PCR amplicon sequencing, and might work OK for you.

CNVkit will work on amplicon sequencing data, and some users have been happy with that application. Its accuracy might not be high enough for your use case, if you're hoping to use the sequencing assay directly to determine treatment for clinical cases without any follow-up testing. A separate PCR-based assay for copy number might be more appropriate for your lab in that case.

[J.F.Jiang]

Yes, I've applied TaqMan assay to directly obtain the CNV status of CYP2D6. There are lots of tools that can be applied on WES, WGS or capture based technology, but not work fine for multiplex PCR based amplicon sequencing.

And most of the tools are designed for somatic, which used segment data for tumor against matched normal ones.

Thanks.

Answer 3

[lffu_0032]

you can try CONVector, it is designed for germinal CNV detection in the PCR-enriched targeted sequencing data. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5075217/pdf/12859_2016_Article_1272.pdf