Structural variants (SVs) are critical contributors to genetic diversity and genomic disease. To predict the phenotypic impact of SVs, there is a need for better estimates of both the occurrence and frequency of SVs, preferably from large, ethnically diverse cohorts. Thus, the current standard approach requires the use of short paired-end reads, which remain challenging to detect, especially at the scale of hundreds to thousands of samples.

中文翻译：

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Parliament2：大规模准确的结构变体调用


结构变异（SV）是遗传多样性和基因组疾病的关键因素。为了预测 SV 的表型影响，需要更好地估计 SV 的发生和频率，最好是来自大型、种族不同的群体。因此，当前的标准方法需要使用短的双端读取，这仍然难以检测，特别是在数百到数千个样本的规模下。