title: Joint detection of copy number variations in parent-offspring trios.
abstract: Whole genome sequencing (WGS) of parent-offspring trios is a powerful approach for identifying disease-associated genes via detecting copy number variations (CNVs). Existing approaches, which detect CNVs for each individual in a trio independently, usually yield low-detection accuracy. Joint modeling approaches leveraging Mendelian transmission within the parent-offspring trio can be an efficient strategy to improve CNV detection accuracy.
  
  
  
  In this study, we developed TrioCNV, a novel approach for jointly detecting CNVs in parent-offspring trios from WGS data. Using negative binomial regression, we modeled the read depth signal while considering both GC content bias and mappability bias. Moreover, we incorporated the family relationship and used a hidden Markov model to jointly infer CNVs for three samples of a parent-offspring trio. Through application to both simulated data and a trio from 1000 Genomes Project, we showed that TrioCNV achieved superior performance than existing approaches.
  
  
  
  The software TrioCNV implemented using a combination of Java and R is freely available from the website at https://github.com/yongzhuang/TrioCNV CONTACT: ydwang@hit.edu.cn
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Yongzhuang
authors.initials: Y
authors.lastname: Liu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Liu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Jianguo
authors.initials: J
authors.lastname: Lu
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Jiajie
authors.initials: J
authors.lastname: Peng
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Liran
authors.initials: L
authors.lastname: Juan
authors.affiliation: Institute for Genomic Medicine, Columbia University, New York, NY 10032, University Program in Genetics and Genomics, Duke University Medical School, Durham, NC 27708.
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Zhu
authors.affiliation: Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235 and Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37235, USA.
authors.forename: Bingshan
authors.initials: B
authors.lastname: Li
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Yadong
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D056915:DNA Copy Number Variations; D016678:Genome; D006801:Humans; D010290:Parents; D012984:Software