摘要： cnvPartition算法在单核苷酸多态性数据上运算时间复杂度较高。为此，提出一种改进的基因拷贝数变异(CNV)检测算法。将二元分割与cnvPartition算法相结合，优先查找显著变异断点，再检测出隐藏性变异断点。实验结果表明，该算法在位点数增加时，最高可提高50%的检测速度，利于检测出小片段的CNV变异。

关键词: 拷贝数变异, cnvPartition算法, 二元分割, 单核苷酸多态性, 环状二元分割, Z检验

Abstract: To solve the problem that the cnvPartition algorithm runs slowly on the Single Nucleotide Polymorphisms(SNP) data, this paper presents an improved gene Copy Number Variation(CNV) detection algorithm, which is combined the binary segmentation algorithm with the cnvPartition algorithm. This algorithm detects the marked breakpoints first, and then is the breakpoints in small copy number variation regions. Experimental results show that the highest of the detection speed of this algorithm can be increased by 50%, and is easy to detect the vignettes of CNV variation.

Key words: Copy Number Variation(CNV), cnvPartition algorithm, binary segmentation, Single Nucleotide Polymorphisms (SNP), Circular Binary Segmentation(CBS), Z-test

中图分类号: 

• TP301.6