| Autor: |
Eliza Cerveira, Kai Ye, Silvia Liu, Adam Mil-homens, Mallory Ryan, Wan-Ping Lee, Charles Lee, Lauren Bellfy, Chengsheng Zhang, Qihui Zhu, Xiaofei Yang |
| Rok vydání: |
2021 |
| Předmět: |
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| DOI: |
10.1101/2021.03.16.21252173 |
| Popis: |
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. The performance of this CNV calling algorithm was evaluated in a blinded manner on 31 samples and compared to the results of clinically-validated CMAs. Comparing to 112 CNVs reported by clinically-validated CMAs of the 31 samples, JAX-CNV is 100% recalling them. Besides, JAX-CNV identified an average of 30 CNVs per individual that is 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 of 4.17%). A robustness test on lower-coverage data revealed a 100% sensitivity for CNVs greater than 300 kb (the current threshold for College of American Pathologists) down to 10x coverage. For CNVs greater 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 100% sensitivity with about 4% false discovery rate. 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 on https://github.com/TheJacksonLaboratory/JAX-CNV. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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