@article{0e44a08d58a14843ad5044eef9f43d81,
title = "Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel",
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, when the target log2 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 multiexon and 29 single-exon CNVs with high C-scores were assessed by Multiplex Ligation-dependent Probe Amplification (MLPA). Conclusion: 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 propose guidelines and criteria to identify high confidence single-exon CNVs.",
keywords = "Atlas-CNV, CNV, copy-number variation, single-exon deletion duplication, targeted gene panel clinical sequencing",
author = "Theodore Chiang and Xiuping Liu and Wu, {Tsung Jung} and Jianhong Hu and Sedlazeck, {Fritz J.} and Simon White and Daniel Schaid and Andrade, {Mariza de} and Jarvik, {Gail P.} and David Crosslin and Ian Stanaway and Carrell, {David S.} and Connolly, {John J.} and Hakon Hakonarson and Groopman, {Emily E.} and Gharavi, {Ali G.} and Alexander Fedotov and Weimin Bi and Leduc, {Magalie S.} and Murdock, {David R.} and Yunyun Jiang and Linyan Meng and Eng, {Christine M.} and Shu Wen and Yaping Yang and Muzny, {Donna M.} and Eric Boerwinkle and William Salerno and Eric Venner and Gibbs, {Richard A.}",
note = "Funding Information: The eMERGE Network phase III work was funded through the following grants: U01HG8657 (Kaiser Permanente Washington, formerly Group Health Cooperative/University of Washington, Seattle); U01HG8685 (Brigham and Women{\textquoteright}s Hospital); U01HG8672 (Vanderbilt University Medical Center); U01HG8666 (Cincinnati Children{\textquoteright}s Hospital Medical Center); U01HG6379 (Mayo Clinic); U01HG8679 (Geisinger Clinic); U01HG8680 (Columbia University Health Sciences); U01HG8684 (Children{\textquoteright}s Hospital of Philadelphia); U01HG8673 (Northwestern University); U01HG8701 (Vanderbilt University Medical Center, serving as the Coordinating Center); U01HG8676 (Partners Healthcare/Broad Institute); and U01HG8664 (Baylor College of Medicine). Funding Information: This work was funded by internal operating funds of the Baylor College of Medicine Human Genome Sequencing Center (HGSC), and by the NIH eMERGE program Phase III: U01HG8657 (Kaiser Permanente Washington/University of Washington); U01HG8685 (Brigham and Women{\textquoteright}s Hospital); U01HG8672 (Vanderbilt University Medical Center); U01HG8666 (Cincinnati Children{\textquoteright}s Hospital Medical Center); U01HG6379 (Mayo Clinic); U01HG8679 (Geisinger Clinic); U01HG8680 (Columbia University Health Sciences); U01HG8684 (Children{\textquoteright}s Hospital of Philadelphia); U01HG8673 (Northwestern University); U01HG8701 (Vanderbilt University Medical Center serving as the Coordinating Center); U01HG8676 (Partners Healthcare/Broad Institute); and U01HG8664 (Baylor College of Medicine). The HGSC is a one of the two Sequencing Centers for the eMERGE III. The Electronic Medical Records and Genomics (eMERGE) Network is a National Human Genome Research Institute (NHGRI)-funded consortium tasked with developing methods and best practices for utilization of the electronic medical record (EMR) as a tool for genomic research. All authors are members of the eMERGE network and declare no conflicts of interest. Publisher Copyright: {\textcopyright} 2019, The Author(s).",
year = "2019",
month = sep,
day = "1",
doi = "10.1038/s41436-019-0475-4",
language = "English (US)",
volume = "21",
pages = "2135--2144",
journal = "Genetics in Medicine",
issn = "1098-3600",
publisher = "Lippincott Williams and Wilkins",
number = "9",
}