首页 > 基因组蛋白质组与生物信息学报（英文版） > Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants

Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants

二维码有效期 120s

摘要Complex structural variants(CSVs)are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants.How-ever,detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy.As a result,there has been limited progress for CSV discovery com-pared with simple structural variants.Here,we systematically analyzed the multi-breakpoint con-nection feature of CSVs,and proposed Mako,utilizing a bottom-up guided model-free strategy,to detect CSVs from paired-end short-read sequencing.Specifically,we implemented a graph-based pattern growth approach,where the graph depicts potential breakpoint connections,and pattern growth enables CSV detection without pre-defined models.Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms.Notably,validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70％,where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp,respectively.Moreover,the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types,including two novel types of adjacent segment swap and tandem dispersed duplication.Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs.Mako is publicly available at https://github.com/xjtu-omics/Mako.

作者 Jiadong Lin ^[1] Xiaofei Yang ^[2] Walter Kosters ^[3] Tun Xu ^[4] Yanyan Jia ^[4] Songbo Wang ^[4] Qihui Zhu ^[5] Mallory Ryan ^[5] Li Guo ^[6] Chengsheng Zhang ^[7] The Human Genome Structural Variation Consortium ^[7] Charles Lee ^[8] Scott E.Devine ^[9] Evan E.Eichler ^[10] Kai Ye 学术成果认领

作者单位 School of Automation Science and Engineering,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Genome Institute,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;Leiden Institute of Advanced Computer Science,Faculty of Science,Leiden University,Leiden 2311EZ,Netherland ^[1] MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;School of Computer Science and Technology,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China ^[2] Leiden Institute of Advanced Computer Science,Faculty of Science,Leiden University,Leiden 2311EZ,Netherland ^[3] School of Automation Science and Engineering,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China ^[4] The Jackson Laboratory for Genomic Medicine,Farmington,CT 06032,USA ^[5] MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China ^[6] The Jackson Laboratory for Genomic Medicine,Farmington,CT 06032,USA;Precision Medicine Center,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China ^[7] School of Automation Science and Engineering,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Institute for Genome Sciences,University of Maryland School of Medicine,Baltimore,MD 21201,USA ^[8] Department of Genome Sciences,University of Washington School of Medicine,Seattle,WA 98119,USA;Howard Hughes Medical Institute,University of Washington,Seattle,WA 98195,USA ^[9] School of Automation Science and Engineering,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;MOE Key Lab for Intelligent Networks&Networks Security,Faculty of Electronic and Information Engineering,Xi'an Jiaotong University,Xi'an 710049,China;Genome Institute,the First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;The School of Life Science and Technology,Xi'an Jiaotong University,Xi'an 710049,China ^[10]

关键词 Next-generation sequencing Complex structural variant Pattern growth Graph mining Formation mechanism

栏目名称

METHOD

发布时间 2022-10-08（万方平台首次上网日期，不代表论文的发表时间）

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交