Estimating genotype error rates from high-coverage next-generation sequence data.
Estimating genotype error rates from high-coverage next-generation sequence data.
复制标题
从高覆盖的下一代序列数据估计基因型错误率。
DOI：
10.1101/gr.168393.113
复制
发表时间：
2014-11
期刊：
影响因子：
7
通讯作者：
Risch N
中科院分区：
文献类型：
--
作者：
Wall JD;Tang LF;Zerbe B;Kvale MN;Kwok PY;Schaefer C;Risch N
外显子组和全基因组测序研究正变得越来越普遍，但对常用平台进行的基因型呼叫的准确性知之甚少。在这里，我们使用来自四个欧美人的血液和唾液DNA样本的重复高覆盖率测序来估计Complete Genomics和Illumina HiSeq全基因组和全外显子组测序的误差率下限。非参考基因型呼叫的错误率从0.1%到0.6%不等，这取决于平台和覆盖深度。此外，我们发现(1)血液和唾液样本之间的错误率或错误率没有差异；(2) Complete Genomics序列的错误率明显高于Illumina序列；(3)对于罕见或独特的变异，错误率更高（高达6%）；(4)误差率一般随基因型质量（GQ）评分而下降，但对于Illumina数据来说是非线性的，可能是由于GQ评分大于60时失去了特异性；(5)错误率随着Illumina数据覆盖深度的增加而增加。这些发现，特别是(3)-(5)表明，在解释基于下一代测序的关联研究结果时应谨慎，在缺乏其他更强大的测序或基因分型方法验证的情况下，在该技术的临床应用中更应谨慎。
Exome and whole-genome sequencing studies are becoming increasingly common, but little is known about the accuracy of the genotype calls made by the commonly used platforms. Here we use replicate high-coverage sequencing of blood and saliva DNA samples from four European-American individuals to estimate lower bounds on the error rates of Complete Genomics and Illumina HiSeq whole-genome and whole-exome sequencing. Error rates for nonreference genotype calls range from 0.1% to 0.6%, depending on the platform and the depth of coverage. Additionally, we found (1) no difference in the error profiles or rates between blood and saliva samples; (2) Complete Genomics sequences had substantially higher error rates than Illumina sequences had; (3) error rates were higher (up to 6%) for rare or unique variants; (4) error rates generally declined with genotype quality (GQ) score, but in a nonlinear fashion for the Illumina data, likely due to loss of specificity of GQ scores greater than 60; and (5) error rates increased with increasing depth of coverage for the Illumina data. These findings, especially (3)–(5), suggest that caution should be taken in interpreting the results of next-generation sequencing-based association studies, and even more so in clinical application of this technology in the absence of validation by other more robust sequencing or genotyping methods.
登录
查看更多内容
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1126/science.1219240
发表时间：
2012-07-06
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Tennessen JA;Bigham AW;O'Connor TD;Fu W;Kenny EE;Gravel S;McGee S;Do R;Liu X;Jun G;Kang HM;Jordan D;Leal SM;Gabriel S;Rieder MJ;Abecasis G;Altshuler D;Nickerson DA;Boerwinkle E;Sunyaev S;Bustamante CD;Bamshad MJ;Akey JM;Broad GO;Seattle GO;NHLBI Exome Sequencing Project
通讯作者：
NHLBI Exome Sequencing Project
影响因子：
14.9
作者：
Nakamura K;Oshima T;Morimoto T;Ikeda S;Yoshikawa H;Shiwa Y;Ishikawa S;Linak MC;Hirai A;Takahashi H;Altaf-Ul-Amin M;Ogasawara N;Kanaya S
通讯作者：
Kanaya S
影响因子：
46.9
作者：
通讯作者：
--
影响因子：
64.8
作者：
通讯作者：
--