IEEE/ACM Trans Comput Biol Bioinform. 2021 Sep-Oct;18(5):1893-1901. doi: 10.1109/TCBB.2019.2954315. Epub 2021 Oct 7.
Next generation sequencing technology has led to the development of methods for the detection of novel sequence insertions (nsINS). Multiple signatures from short reads are usually extracted to improve nsINS detection performance. However, characterization of nsINSs larger than the mean insert size is still challenging. This article presents a new method, ERINS, to detect nsINS contents and genotypes of full spectrum range size. It integrates the features of structural variations and mapping states of split reads to find nsINS breakpoints, and then adopts a left-most mapping strategy to infer nsINS content by iteratively extending the standard reference at each breakpoint. Finally, it realigns all reads to the extended reference and infers nsINS genotypes through statistical testing on read counts. We test and validate the performance of ERINS on simulation and real sequencing datasets. The simulation experimental results demonstrate that it outperforms several peer methods with respect to sensitivity and precision. The real data application indicates that ERINS obtains high consistent results with those of previously reported and detects nsINSs over 200 base pairs that many other methods fail. In conclusion, ERINS can be used as a supplement to existing tools and will become a routine approach for characterizing nsINSs.
下一代测序技术已经开发出了用于检测新序列插入（nsINS）的方法。通常会提取来自短读长的多个特征来提高 nsINS 检测性能。然而，大于平均插入大小的 nsINS 的特征描述仍然具有挑战性。本文提出了一种新的方法 ERINS，用于检测全谱范围大小的 nsINS 内容和基因型。它集成了结构变异的特征和分裂读的映射状态，以找到 nsINS 的断点，然后采用最左映射策略，通过在每个断点处迭代扩展标准参考来推断 nsINS 内容。最后，它将所有读重新比对到扩展的参考，并通过对读计数进行统计检验来推断 nsINS 基因型。我们在模拟和真实测序数据集上测试和验证了 ERINS 的性能。模拟实验结果表明，它在灵敏度和精度方面优于几个同类方法。实际数据应用表明，ERINS 与先前报道的结果高度一致，并检测到了许多其他方法无法检测到的超过 200 个碱基对的 nsINS。总之，ERINS 可以作为现有工具的补充，并将成为特征描述 nsINS 的常规方法。
