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Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel
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 with...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752313/ https://www.ncbi.nlm.nih.gov/pubmed/30890783 http://dx.doi.org/10.1038/s41436-019-0475-4 |
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author | Chiang, Theodore Liu, Xiuping Wu, Tsung-Jung Hu, Jianhong Sedlazeck, Fritz J. White, Simon Schaid, Daniel Andrade, Mariza de Jarvik, Gail P. Crosslin, David Stanaway, Ian Carrell, David S. Connolly, John J. Hakonarson, Hakon Groopman, Emily E. Gharavi, Ali G. Fedotov, Alexander Bi, Weimin Leduc, Magalie S. Murdock, David R. Jiang, Yunyun Meng, Linyan Eng, Christine M. Wen, Shu Yang, Yaping Muzny, Donna M. Boerwinkle, Eric Salerno, William Venner, Eric Gibbs, Richard A. |
author_facet | Chiang, Theodore Liu, Xiuping Wu, Tsung-Jung Hu, Jianhong Sedlazeck, Fritz J. White, Simon Schaid, Daniel Andrade, Mariza de Jarvik, Gail P. Crosslin, David Stanaway, Ian Carrell, David S. Connolly, John J. Hakonarson, Hakon Groopman, Emily E. Gharavi, Ali G. Fedotov, Alexander Bi, Weimin Leduc, Magalie S. Murdock, David R. Jiang, Yunyun Meng, Linyan Eng, Christine M. Wen, Shu Yang, Yaping Muzny, Donna M. Boerwinkle, Eric Salerno, William Venner, Eric Gibbs, Richard A. |
author_sort | Chiang, Theodore |
collection | PubMed |
description | 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 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 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. |
format | Online Article Text |
id | pubmed-6752313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-67523132019-09-23 Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel Chiang, Theodore Liu, Xiuping Wu, Tsung-Jung Hu, Jianhong Sedlazeck, Fritz J. White, Simon Schaid, Daniel Andrade, Mariza de Jarvik, Gail P. Crosslin, David Stanaway, Ian Carrell, David S. Connolly, John J. Hakonarson, Hakon Groopman, Emily E. Gharavi, Ali G. Fedotov, Alexander Bi, Weimin Leduc, Magalie S. Murdock, David R. Jiang, Yunyun Meng, Linyan Eng, Christine M. Wen, Shu Yang, Yaping Muzny, Donna M. Boerwinkle, Eric Salerno, William Venner, Eric Gibbs, Richard A. Genet Med Article 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 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 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. Nature Publishing Group US 2019-03-20 2019 /pmc/articles/PMC6752313/ /pubmed/30890783 http://dx.doi.org/10.1038/s41436-019-0475-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. If you remix, transform, or build upon this article or a part thereof, you must distribute your contributions under the same license as the original. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/. |
spellingShingle | Article Chiang, Theodore Liu, Xiuping Wu, Tsung-Jung Hu, Jianhong Sedlazeck, Fritz J. White, Simon Schaid, Daniel Andrade, Mariza de Jarvik, Gail P. Crosslin, David Stanaway, Ian Carrell, David S. Connolly, John J. Hakonarson, Hakon Groopman, Emily E. Gharavi, Ali G. Fedotov, Alexander Bi, Weimin Leduc, Magalie S. Murdock, David R. Jiang, Yunyun Meng, Linyan Eng, Christine M. Wen, Shu Yang, Yaping Muzny, Donna M. Boerwinkle, Eric Salerno, William Venner, Eric Gibbs, Richard A. Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title | Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title_full | Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title_fullStr | Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title_full_unstemmed | Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title_short | Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel |
title_sort | atlas-cnv: a validated approach to call single-exon cnvs in the emergeseq gene panel |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6752313/ https://www.ncbi.nlm.nih.gov/pubmed/30890783 http://dx.doi.org/10.1038/s41436-019-0475-4 |
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