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• W2893227359 abstract "Abstract 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 batch of samples (midpool), when the target log 2 ratio of the sample to the batch 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." @default.
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• W2893227359 date "2018-09-27" @default.
• W2893227359 modified "2023-10-15" @default.
• W2893227359 title "Atlas-CNV: a validated approach to call Single-Exon CNVs in the eMERGESeq gene panel" @default.
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• W2893227359 doi "https://doi.org/10.1101/422337" @default.
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