Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.
Comparison of sequencing based CNV discovery methods using monozygotic twin quartets.
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DOI：
10.1371/journal.pone.0122287
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Dubé MP
中科院分区：
文献类型：
--
作者：
Legault MA;Girard S;Lemieux Perreault LP;Rouleau GA;Dubé MP
高通量测序方法的出现带来了大量的技术挑战。其中之一是利用全基因组测序数据发现拷贝数变异（CNV）而引发的问题。 CNV 是基因组结构变异，定义为大基因组片段（通常超过 1 KB）拷贝数的变异。在这里，我们的目的是比较不同的 CNV 识别方法，通过比较 9 个同卵双胞胎中的识别方法来评估它们一致识别 CNV 的能力。使用同卵双胞胎提供了一种通过观察在考虑孟德尔遗传规则和双胞胎之间基因组相同的假设时不一致调用的 CNV 来估计每种算法的错误率的方法。还考虑了来自不同工具的调用之间的相似性以及组合调用集的优势。当考虑遗传 CNV 率时，ERDS 和 CNVnator 获得了最佳性能，平均值分别为 0.74 和 0.70。生成维恩图来显示不同算法之间在过滤掉家族不一致之前和之后的一致性。此过滤揭示了 CNVer 和 Breakdancer 的大量误报。这些方法之间的总体一致性较低，表明在调用 CNV 时不同工具具有高度互补性。断点敏感性分析表明，CNVnator 和 ERDS 比其他工具实现了更好的 CNV 边界分辨率。通过这两种工具的交叉实现了最高的遗传性 CNV 率 (81%)。这项研究表明，ERDS 和 CNVnator 在全基因组测序数据上在跨家族的 CNV 一致性、CNV 断点分辨率和 CNV 调用特异性方面提供了良好的性能。这两个工具的调用交叉对于 CNV 基因分型流程非常有价值。
The advent of high throughput sequencing methods breeds an important amount of technical challenges. Among those is the one raised by the discovery of copy-number variations (CNVs) using whole-genome sequencing data. CNVs are genomic structural variations defined as a variation in the number of copies of a large genomic fragment, usually more than one kilobase. Here, we aim to compare different CNV calling methods in order to assess their ability to consistently identify CNVs by comparison of the calls in 9 quartets of identical twin pairs. The use of monozygotic twins provides a means of estimating the error rate of each algorithm by observing CNVs that are inconsistently called when considering the rules of Mendelian inheritance and the assumption of an identical genome between twins. The similarity between the calls from the different tools and the advantage of combining call sets were also considered. ERDS and CNVnator obtained the best performance when considering the inherited CNV rate with a mean of 0.74 and 0.70, respectively. Venn diagrams were generated to show the agreement between the different algorithms, before and after filtering out familial inconsistencies. This filtering revealed a high number of false positives for CNVer and Breakdancer. A low overall agreement between the methods suggested a high complementarity of the different tools when calling CNVs. The breakpoint sensitivity analysis indicated that CNVnator and ERDS achieved better resolution of CNV borders than the other tools. The highest inherited CNV rate was achieved through the intersection of these two tools (81%). This study showed that ERDS and CNVnator provide good performance on whole genome sequencing data with respect to CNV consistency across families, CNV breakpoint resolution and CNV call specificity. The intersection of the calls from the two tools would be valuable for CNV genotyping pipelines.
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