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. 2017 Jul;38(7):889-897.
doi: 10.1002/humu.23237. Epub 2017 May 16.

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

Gundula Povysil  1 , Antigoni Tzika  2 , Julia Vogt  2 , Verena Haunschmid  1 , Ludwine Messiaen  3 , Johannes Zschocke  2 , Günter Klambauer  1 , Sepp Hochreiter  1 , Katharina Wimmer  2
Affiliations

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

Gundula Povysil et al. Hum Mutat. 2017 Jul.

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.

Keywords: clinical diagnostics; copy-number variation; deletion; duplication; panel sequencing; targeted next-generation sequencing.

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Figures

Figure 1
Figure 1
panelcn.MOPS analysis pipeline. The input to panelcn.MOPS is a BAM file for every sample and the corresponding BED file. The final output is a table of results and boxplots of the normalized RCs for user‐selected genes of interest
Figure 2
Figure 2
Boxplot of normalized RCs. The normalized RCs of the test sample and all controls used are displayed as boxplots for each ROI (exons numbered in consecutive order according to BED file) of the NF1 gene. The RCs of each control sample are symbolized by black dots, whereas the RCs of the test sample are highlighted by red dots. The deletion of all ROIs is clearly visible by the red dots that are distinctly below the boxes and whiskers
Figure 3
Figure 3
Strengths and weaknesses of all methods analyzed. In general, “+++” indicates the best possible performance, whereas “++” means the method is close to the best, “+” is acceptable, but not very good, and “−” signals failure or missing feature. For the two detection performance measures (i.e., sensitivity and specificity), 100% is indicated by “+++.” A single FN or FP is indicated by “++” in the corresponding sensitivity or specificity row. More than one false classification but an overall sensitivity or specificity greater than 95% is indicated by “+.” “No‐call rate” stands for the fraction of ROIs classified as low quality (see the section “Evaluation criteria”). “+++” means no‐call rate of 0, “++” means less than 0.01, “+” means less than 0.1, and “−” means no‐call rate larger than 0.1. Programs with QC for samples and ROIs are marked as “+++,” whereas programs with QC only for samples are marked as “+.” For “CNVs <1 ROI,” each plus sign symbolizes one successful detection of a CNV that affected only part of a ROI (see the section “Small CNVs”). The row “Whole‐gene CNVs” especially concerns CNVs that affect all ROIs that are within the gene of interest for a patient. “+++” indicates that all of them were detected, whereas “++” indicates that some of them were detected and others classified as low quality. If the CNVs affecting the entire gene of interest are not fully detected, this is indicated by “+,” whereas “−” means that these CNVs can only be detected while risking incidental findings. While “+” in the row “Incidental findings” indicates that incidental findings can be avoided, but only at the risk of missing CNVs that affect all ROIs analyzed, “+++” means that the method avoids incidental findings without loss of power. “−” reflects that the CNV tool offers no option to filter the results for genes of interest and, therefore, for avoiding incidental findings. The row “Runtime” indicates the runtime of the CNV detection algorithm measured as described in the section “Runtime.” The thresholds for “+++,” “++,” “+,” and “−” are less than 10 min, less than 1 hr, less than 6 hr, and more than 6 hr, respectively. Classes for the row “GUI” are: “+++” if there is an easy‐to‐use graphical user interface (GUI), “++” if the GUI is not easy to use, and “−” if there is no GUI at all. Since only two of the programs are commercial, they were marked “−” in the corresponding row, whereas all others have “+++”
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