panelcn.MOPS: Copy number detection in targeted NGS panel data for clinical diagnostics

Abstract

Targeted next-generation-sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy number variations (CNVs) in addition to single-nucleotide-variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control, incidental findings, and user-friendliness.

We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with 5 state-of-the-art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region-of-interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user-selected genes, thus, avoiding incidental findings. Additionally, panelcn.MOPS offers quality control criteria not only for samples but also for individual ROIs within a sample which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience.

panelcn.MOPS combines high sensitivity and specificity with user-friendliness rendering it highly suitable for routine clinical diagnostics.

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