Journal
GENOMICS PROTEOMICS & BIOINFORMATICS
Volume 20, Issue 6, Pages 1197-1206Publisher
ELSEVIER
DOI: 10.1016/j.gpb.2021.06.003
Keywords
Copy number variant; Chromosomal microarray assay; Whole-genome sequencing; JAX-CNV; Genetic testing
Categories
Funding
- First Affiliated Hospital of Xi'an Jiaotong University, China
- National Institutes of Health, USA [U24AG041689, U54AG052427]
- National Natural Science Foundation of China [61702406, 31671372]
- National Science and Technology Major Project of China [2018ZX10302205]
- National Key R&D Program of China [2018YFC0910400, 2017YFC0907500]
- China Postdoctoral Science Foundation [2017M623178]
- Ewha WomansUniversity Research, South Korea [2018-2019]
- Connecticut Bio-Innovative Fund, USA
Ask authors/readers for more resources
This study aimed to develop a CNV calling algorithm based on whole-genome sequencing that could replace the use of chromosomal microarray assay (CMA) in clinical diagnosis. The algorithm, called JAX-CNV, demonstrated excellent performance, with a false discovery rate of 4% and the ability to detect CNVs even at low coverage.
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, representing 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 kb (the current threshold for College of American Pathologists) down to 10x coverage. For CNVs larger than 50 kb, sensitivities were 100% for coverages deeper than 20x, 97% for 15x, and 95% for 10x. 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available