Document Type

Article

Publication Date

12-1-2022

Publication Title

Genomics, proteomics & bioinformatics

Keywords

JGM, Chromosomal microarray assay, Copy number variant, Genetic testing, JAX-CNV, Whole-genome sequencing

JAX Location

Genomics Proteomics Bioinformatics. 2022 Dec;20(6):1197-1206.

Volume

20

Issue

6

First Page

1197

Last Page

1206

PMID

35085778

DOI

10.1016/j.gpb.2021.06.003

Grant

We would like to thank Drs. Zirui Dong and Yukyung Jun fortheir work on Figures 2 and 4. We would also like to thankDrs. Jee Young Kwon and Won Yeong Kang for their work onthe manuscript revision. This study is supported in part by theoperational funds from The First Affiliated Hospital of Xi’anJiaotong University, China. WL is supported by the NationalInstitutes of Health, USA (Grant Nos. U24AG041689 andU54AG052427). XY and KY are supported by the National Nat-ural Science Foundation of China (Grant Nos. 61702406 and31671372), the National Science and Technology Major Projectof China (Grant No. 2018ZX10302205), the National KeyR&D Program of China (Grant Nos. 2018YFC0910400 and2017YFC0907500), and the General Financial Grant from theChina Postdoctoral Science Foundation (Grant No.2017M623178). CL was a distinguished Ewha Womans Univer-sity Professor supported in part by the Ewha Womans UniversityResearch, South Korea (Grant No. 2018-2019). CZ was sup-ported in part by the Connecticut Bio-Innovative Fund, USA.

Abstract

We aimed to develop a whole-genome sequencing (WGS)-based copy number variant (CNV) calling algorithm with the potential of replacing chromosomal microarray assay (CMA) for clinical diagnosis. JAX-CNV is thus developed for CNV detection from WGS data. The performance of this CNV calling algorithm was evaluated in a blinded manner on 31 samples and compared to the 112 CNVs reported by clinically validated CMAs for these 31 samples. The result showed that JAX-CNV recalled 100% of these CNVs. Besides, JAX-CNV identified an average of 30 CNVs per individual, respresenting an approximately seven-fold increase compared to calls of clinically validated CMAs. Experimental validation of 24 randomly selected CNVs showed one false positive, i.e., a false discovery rate (FDR) of 4.17%. A robustness test on lower-coverage data revealed a 100% sensitivity for CNVs larger than 300‚ÄØkb (the current threshold for College of American Pathologists) down to 10√ó coverage. For CNVs larger than 50‚ÄØkb, sensitivities were 100% for coverages deeper than 20√ó, 97% for 15√ó, and 95% for 10√ó. We developed a WGS-based CNV pipeline, including this newly developed CNV caller JAX-CNV, and found it capable of detecting CMA-reported CNVs at a sensitivity of 100% with about a FDR of 4%. We propose that JAX-CNV could be further examined in a multi-institutional study to justify the transition of first-tier genetic testing from CMAs to WGS. JAX-CNV is available at https://github.com/TheJacksonLaboratory/JAX-CNV.

Comments

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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