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

Academic Article

Abstract

  • © 2017 The Authors. Human Mutation published by Wiley Periodicals, Inc. 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.
  • Published In

  • Human Mutation  Journal
  • Digital Object Identifier (doi)

    Author List

  • Povysil G; Tzika A; Vogt J; Haunschmid V; Messiaen L; Zschocke J; Klambauer G; Hochreiter S; Wimmer K
  • Start Page

  • 889
  • End Page

  • 897
  • Volume

  • 38
  • Issue

  • 7