An accurate and powerful method for copy number variation detection
An accurate and powerful method for copy number variation detection
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DOI：
10.1093/bioinformatics/bty1041
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发表时间：
2019-01
期刊：
影响因子：
5.8
通讯作者：
Feifei Xiao;Xizhi Luo;Ning Hao;Yue Niu;Xiangjun Xiao;G. Cai;C. Amos;Heping Zhang
中科院分区：
文献类型：
--
作者：
Feifei Xiao;Xizhi Luo;Ning Hao;Yue Niu;Xiangjun Xiao;G. Cai;C. Amos;Heping Zhang
将多遗传源整合到拷贝数变异检测（CNV）中是提高复杂性状相关变异识别的有效方法。尽管广泛使用的基于变化点的方法可以提高识别变异的统计能力，但由于基因分型强度数据的噪声性质，有效检测具有弱信号的CNVs仍然具有挑战性。我们之前开发了一种基于正态均值的筛选和排序算法模型modSaRa，该模型具有良好的灵敏度和较高的计算效率。为了提高变异识别的统计能力，我们提出了一种新的改进方法，将相对等位基因强度与来自经验统计的外部信息与建模相结合，我们称之为modSaRa2。结果模拟研究表明，与现有的基于阵列的数据分析方法相比，modSaRa2的灵敏度和特异性都有显著提高。弱CNV信号检测的改进最为显著，同时也提高了CNV大小变化时的稳定性。将新方法应用于黑色素瘤全基因组数据集，发现了新的候选黑色素瘤风险相关的染色体带1p22.2缺失和6p22、6q25和19p13区域的重复，这可能有助于理解种系拷贝数变异在黑色素瘤病因学中的可能作用。可用性http://c2s2.yale.edu/software/modSaRa2或https://github.com/FeifeiXiaoUSC/modSaRa2。补充信息补充数据可在Bioinformatics网站在线获得。
Motivation Integration of multiple genetic sources for copy number variation detection (CNV) is a powerful approach to improve the identification of variants associated with complex traits. Although it has been shown that the widely used change point based methods can increase statistical power to identify variants, it remains challenging to effectively detect CNVs with weak signals due to the noisy nature of genotyping intensity data. We previously developed modSaRa, a normal mean-based model on a screening and ranking algorithm for copy number variation identification which presented desirable sensitivity with high computational efficiency. To boost statistical power for the identification of variants, here we present a novel improvement that integrates the relative allelic intensity with external information from empirical statistics with modeling, which we called modSaRa2. Results Simulation studies illustrated that modSaRa2 markedly improved both sensitivity and specificity over existing methods for analyzing array-based data. The improvement in weak CNV signal detection is the most substantial, while it also simultaneously improves stability when CNV size varies. The application of the new method to a whole genome melanoma dataset identified novel candidate melanoma risk associated deletions on chromosome bands 1p22.2 and duplications on 6p22, 6q25, and 19p13 regions, which may facilitate the understanding of the possible roles of germline copy number variants in the etiology of melanoma. Availability http://c2s2.yale.edu/software/modSaRa2 or https://github.com/FeifeiXiaoUSC/modSaRa2. Supplementary information Supplementary data are available at Bioinformatics online.