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	Pysim-sv: a package for simulating structural variation data with GC-biases
	Xia, Yuchao ; Liu, Yun ; Deng, Minghua ; Xi, Ruibin
	2017
关键词	Copy number variation Translocation Breakpoints Next-generation sequencing SOMATIC MUTATIONS CANCER FRAMEWORK CATALOG GENOMES
英文摘要	Background: Structural variations (SVs) are wide-spread in human genomes and may have important implications in disease-related and evolutionary studies. High-throughput sequencing (HTS) has become a major platform for SV detection and simulation serves as a powerful and cost-effective approach for benchmarking SV detection algorithms. Accurate performance assessment by simulation requires the simulator capable of generating simulation data with all important features of real data, such GC biases in HTS data and various complexities in tumor data. However, no available package has systematically addressed all issues in data simulation for SV benchmarking. Results: Pysim-sv is a package for simulating HTS data to evaluate performance of SV detection algorithms. Pysim-sv can introduce a wide spectrum of germline and somatic genomic variations. The package contains functionalities to simulate tumor data with aneuploidy and heterogeneous subclones, which is very useful in assessing algorithm performance in tumor studies. Furthermore, Pysim-sv can introduce GC-bias, the most important and prevalent bias in HTS data, in the simulated HTS data. Conclusions: Pysim-sv provides an unbiased toolkit for evaluating HTS-based SV detection algorithms.; National Key Basic Research Project of China [2015CB856000]; National Natural Science Foundation of China [11471022, 71532001]; Recruitment Program of Global Youth Experts of China; SCI(E); ARTICLE; 18
语种	英语
出处	SCI
出版者	BMC BIOINFORMATICS
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/474595]
专题	数学科学学院
推荐引用方式 GB/T 7714	Xia, Yuchao,Liu, Yun,Deng, Minghua,et al. Pysim-sv: a package for simulating structural variation data with GC-biases. 2017-01-01.

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