Structural variation (SV), involving deletions, duplications, insertions and inversions of DNA segments, accounts for a large proportion of human genetic diversity. Comprehensive identification and analysis of these genetic variants will help us more fully elucidate the biology of their functional effects on human health and demography. Despite recent advances, the tools and data needed to comprehensively identify all types of SVs, genotype each variant, integrate and phase these variants remain lacking. Indeed, the data released from the early phases of the 1000 Genomes Project (1000GP) (1000 Genomes Project Consortium, 2010;1000 Genomes Project Consortium, 2012) are biased primarily towards the detection of deletions within relatively unique regions of the genome. As a consortium, we propose to pool expertise from various research groups to provide an integrative analysis of SVs by combining rigorous computational algorithmic development with extensive experimental validation. The new algorithms we develop and the high confidence lists of SVs obtained will be rapidly made available as a public resource.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Biotechnology Resource Cooperative Agreements (U41)
Project #
Application #
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Brooks, Lisa
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Jackson Laboratory
Bar Harbor
United States
Zip Code
Becker, Timothy; Lee, Wan-Ping; Leone, Joseph et al. (2018) FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods. Genome Biol 19:38
Antaki, Danny; Brandler, William M; Sebat, Jonathan (2018) SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes. Bioinformatics 34:1774-1777
Zhang, Yan; Li, Shantao; Abyzov, Alexej et al. (2017) Landscape and variation of novel retroduplications in 26 human populations. PLoS Comput Biol 13:e1005567
Fan, Xian; Chaisson, Mark; Nakhleh, Luay et al. (2017) HySA: a Hybrid Structural variant Assembly approach using next-generation and single-molecule sequencing technologies. Genome Res 27:793-800
Chong, Zechen; Ruan, Jue; Gao, Min et al. (2017) novoBreak: local assembly for breakpoint detection in cancer genomes. Nat Methods 14:65-67
Porubsky, David; Garg, Shilpa; Sanders, Ashley D et al. (2017) Dense and accurate whole-chromosome haplotyping of individual genomes. Nat Commun 8:1293
Harmanci, Arif; Gerstein, Mark (2016) Quantification of private information leakage from phenotype-genotype data: linking attacks. Nat Methods 13:251-6
Brandler, William M; Antaki, Danny; Gujral, Madhusudan et al. (2016) Frequency and Complexity of De Novo Structural Mutation in Autism. Am J Hum Genet 98:667-79
Tai, Derek J C; Ragavendran, Ashok; Manavalan, Poornima et al. (2016) Engineering microdeletions and microduplications by targeting segmental duplications with CRISPR. Nat Neurosci 19:517-22
Hehir-Kwa, Jayne Y; Marschall, Tobias; Kloosterman, Wigard P et al. (2016) A high-quality human reference panel reveals the complexity and distribution of genomic structural variants. Nat Commun 7:12989

Showing the most recent 10 out of 26 publications