JAX-CNV:A Whole-genome Sequencing-based Algorithm for Copy Number Detection at Clinical Grade Level  

作　　者：Wan-Ping Lee Qihui Zhu Xiaofei Yang Silvia Liu Eliza Cerveira Mallory Ryan Adam Mil-Homens Lauren Bellfy Kai Ye Charles Lee Chengsheng Zhang 

机构地区：[1]Precision Medicine Center,The First Affiliated Hospital of Xi’an Jiaotong University,Xi’an 710061,China [2]The Jackson Laboratory for Genomic Medicine,Farmington,CT 06032,USA [3]School of Cyber Science and Engineering,Xi’an Jiaotong University,Xi’an 710049,China [4]Department of Pathology and Laboratory Medicine,Perelman School of Medicine,University of Pennsylvania,Philadelphia,PA 19104,USA [5]School of Computer Science and Technology,Faculty of Electronic and Information Engineering,Xi’an Jiaotong University,Xi’an 710049,China [6]MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi’an Jiaotong University,Xi’an 710049,China [7]Department of Life Sciences,Ewha Womans University,Seoul 03760,South Korea

出　　处：《Genomics, Proteomics & Bioinformatics》2022年第6期1197-1206,共10页基因组蛋白质组与生物信息学报（英文版）

基　　金：supported in part by the operational funds from The First Affiliated Hospital of Xi’an Jiaotong University, China;supported by the National Institutes of Health, USA (Grant Nos. U24AG041689 and U54AG052427);supported by the National Natural Science Foundation of China (Grant Nos. 61702406 and 31671372);the National Science and Technology Major Project of China (Grant No. 2018ZX10302205);the National Key R&D Program of China (Grant Nos. 2018YFC0910400 and 2017YFC0907500);the General Financial Grant from the China Postdoctoral Science Foundation (Grant No. 2017M623178);supported in part by the Ewha Womans University Research, South Korea (Grant No. 2018-2019);supported in part by the Connecticut Bio-Innovative Fund, USA

摘　　要：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 lowercoverage 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,sensitivities 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/TheJacksonLaboratory/JAX-CNV.

关 键 词：Copy number variant Chromosomal microarray assay Whole-genome sequencing JAX-CNV Genetic testing 

分 类 号：Q811.4[生物学—生物工程]