SCIP: software for efficient clinical interpretation of copy number variants detected by whole-genome sequencing

被引:0
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作者
Qiliang Ding
Cherith Somerville
Roozbeh Manshaei
Brett Trost
Miriam S. Reuter
Kelsey Kalbfleisch
Kaitlin Stanley
John B. A. Okello
S. Mohsen Hosseini
Eriskay Liston
Meredith Curtis
Mehdi Zarrei
Edward J. Higginbotham
Ada J. S. Chan
Worrawat Engchuan
Bhooma Thiruvahindrapuram
Stephen W. Scherer
Raymond H. Kim
Rebekah K. Jobling
机构
[1] Cardiac Genome Clinic,Ted Rogers Centre for Heart Research
[2] The Hospital for Sick Children,Division of Clinical and Metabolic Genetics
[3] The Hospital for Sick Children,The Centre for Applied Genomics
[4] The Hospital for Sick Children,Program in Genetics and Genome Biology
[5] The Hospital for Sick Children,CGEn
[6] The Hospital for Sick Children,MIT Sloan School of Management
[7] Massachusetts Institute of Technology,Department of Pathology
[8] The University of Texas MD Anderson Cancer Center,Genome Diagnostics, Department of Paediatric Laboratory Medicine
[9] The Hospital for Sick Children,Department of Molecular Genetics and the McLaughlin Centre
[10] University of Toronto,Fred A. Litwin Family Centre in Genetic Medicine
[11] University Health Network,Department of Medicine
[12] University of Toronto,undefined
来源
Human Genetics | 2023年 / 142卷
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摘要
Copy number variants (CNVs) represent major etiologic factors in rare genetic diseases. Current clinical CNV interpretation workflows require extensive back-and-forth with multiple tools and databases. This increases complexity and time burden, potentially resulting in missed genetic diagnoses. We present the Suite for CNV Interpretation and Prioritization (SCIP), a software package for the clinical interpretation of CNVs detected by whole-genome sequencing (WGS). The SCIP Visualization Module near-instantaneously displays all information necessary for CNV interpretation (variant quality, population frequency, inheritance pattern, and clinical relevance) on a single page—supported by modules providing variant filtration and prioritization. SCIP was comprehensively evaluated using WGS data from 1027 families with congenital cardiac disease and/or autism spectrum disorder, containing 187 pathogenic or likely pathogenic (P/LP) CNVs identified in previous curations. SCIP was efficient in filtration and prioritization: a median of just two CNVs per case were selected for review, yet it captured all P/LP findings (92.5% of which ranked 1st). SCIP was also able to identify one pathogenic CNV previously missed. SCIP was benchmarked against AnnotSV and a spreadsheet-based manual workflow and performed superiorly than both. In conclusion, SCIP is a novel software package for efficient clinical CNV interpretation, substantially faster and more accurate than previous tools (available at https://github.com/qd29/SCIP, a video tutorial series is available at https://bit.ly/SCIPVideos).
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页码:201 / 216
页数:15
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