JAX-CNV:A Whole-genome Sequencing-based Algorithm for Copy Number Detection at Clinical Grade Level
- Author:
Lee WAN-PING
1
;
Zhu QIHUI
;
Yang XIAOFEI
;
Liu SILVIA
;
Cerveira ELIZA
;
Ryan MALLORY
;
Mil-Homens ADAM
;
Bellfy LAUREN
;
Ye KAI
;
Lee CHARLES
;
Zhang CHENGSHENG
Author Information
1. Precision Medicine Center,The First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;The Jackson Laboratory for Genomic Medicine,Farmington,CT 06032,USA;School of Cyber Science and Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Department of Pathology and Laboratory Medicine,Perelman School of Medicine,University of Pennsylvania,Philadelphia,PA 19104,USA
- Keywords:
Copy number variant;
Chromosomal microarray assay;
Whole-genome sequencing;
JAX-CNV;
Genetic testing
- From:
Genomics, Proteomics & Bioinformatics
2022;(6):1197-1206
- CountryChina
- Language:Chinese
-
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 perfor-mance of this CNV calling algorithm was evaluated in a blinded manner on 31 samples and com-pared 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 10×coverage.For CNVs larger than 50 kb,sensi-tivities were 100％for coverages deeper than 20×,97％for 15×,and 95％for 10×.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/The J acksonLaboratory/JAX-CNV.
