Empirical evaluation of variant calling accuracy using ultra-deep whole-genome sequencing data
Empirical evaluation of variant calling accuracy using ultra-deep whole-genome sequencing data
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DOI：
10.1038/s41598-018-38346-0
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发表时间：
2019-02-11
影响因子：
4.6
通讯作者：
Okada, Yukinori
中科院分区：
文献类型：
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作者：
Kishikawa, Toshihiro;Momozawa, Yukihide;Okada, Yukinori
在全基因组测序（WGS）研究的设计中，测序深度是定义变异调用准确性和研究成本的关键参数，目前尚无标准建议。我们使用超深WGS数据对WGS管道的变量调用精度进行了实证评估（大约410倍）。我们随机抽取序列读数，并构建了一系列具有不同渐变深度的模拟WGS数据集（n = 54，从0.05 x到410 x）。接下来，我们使用所有的序列读取来评估WGS数据与SNP微阵列数据或WGS数据的基因型一致性。此外，我们使用多个软件工具（PHLAT、HLA- vbseq、HLA- hd和SNP2HLA）利用WGS数据评估HLA等位基因分型的准确性。深度越深的WGS资料一致性率越高，>13.7 x深度的资料一致性率高达>99%。使用所有序列reads与WGS数据的比较表明，snv在17.6 x深度下达到了约95%的一致性，而索引只有60%的一致性。对于使用WGS数据进行HLA等位基因分型的准确性，13.7 x深度显示了足够的准确性，但观察到软件工具之间的性能异质性（HLA- hd的一致性最高为96.9%）。进一步增加深度对HLA基因分型准确性的提高是有限的。这些结果表明，中等程度的WGS深度设置（约15倍）可以实现准确的SNV呼叫和成本效益，而精确的indel呼叫需要相对较高的深度。
In the design of whole-genome sequencing (WGS) studies, sequencing depth is a crucial parameter to define variant calling accuracy and study cost, with no standard recommendations having been established. We empirically evaluated the variant calling accuracy of the WGS pipeline using ultra-deep WGS data (approximately 410x). We randomly sampled sequence reads and constructed a series of simulation WGS datasets with a variety of gradual depths (n = 54; from 0.05 x to 410 x). Next, we evaluated the genotype concordances of the WGS data with those in the SNP microarray data or the WGS data using all the sequence reads. In addition, we assessed the accuracy of HLA allele genotyping using the WGS data with multiple software tools (PHLAT, HLA-VBseq, HLA-HD, and SNP2HLA). The WGS data with higher depths showed higher concordance rates, and >13.7 x depth achieved as high as >99% of concordance. Comparisons with the WGS data using all the sequence reads showed that SNVs achieved >95% of concordance at 17.6 x depth, whereas indels showed only 60% concordance. For the accuracy of HLA allele genotyping using the WGS data, 13.7 x depth showed sufficient accuracy while performance heterogeneity among the software tools was observed (the highest concordance of 96.9% was observed with HLA-HD). Improvement in HLA genotyping accuracy by further increasing the depths was limited. These results suggest a medium degree of the WGS depth setting (approximately 15 x) to achieve both accurate SNV calling and cost-effectiveness, whereas relatively higher depths are required for accurate indel calling.