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

G. Povsil, A. Tzika, J. Vogt, V. Haunschmid, L. Messiaen, J. Zschocke, G. Klambauer, S. Hochreiter, K. Wimmer. panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics. Human Mutation, volume 38, number 7, pages 889-897, DOI 10.1002/humu.23237, 7, 2017.

Autoren
  • Gundula Povsil
  • Antigoni Tzika
  • Julia Vogt
  • Verena Haunschmid
  • Ludwine Messiaen
  • Johannes Zschocke
  • Günter Klambauer
  • Sepp Hochreiter
  • Katharina Wimmer
TypArtikel
JournalHuman Mutation
Nummer7
Band38
DOI10.1002/humu.23237
Monat7
Jahr2017
Seiten889-897
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 (QC), 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 five 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 QC 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.