Atlas-CNV: a validated approach to call Single-Exon CNVs in the eMERGESeq gene panel
Fritz J Sedlazeck,
Mariza de Andrade,
Gail P Jarvik,
David S Carrell,
John J Connolly,
Emily E Groopman,
Ali G Gharavi,
Magalie S Leduc,
David R. Murdock,
Christine M Eng,
Donna M. Muzny,
William J. Salerno,
Richard A. Gibbs
Posted 27 Sep 2018
bioRxiv DOI: 10.1101/422337 (published DOI: 10.1038/s41436-019-0475-4)
Posted 27 Sep 2018
Purpose: To provide a validated method to confidently identify exon-containing copy number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs. Methods: DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a midpool batch, when the target log2 ratio of the sample to the midpool median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap). Results: Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multi-exon and 29 single-exon CNVs with high C-scores were assessed by MLPA. Conclusions: Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We proposed guidelines and criteria to identify high confidence single-exon CNVs. Key Words: Atlas-CNV; copy number variation; CNV; single exon deletion duplication; targeted gene panel clinical sequencing;
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