Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing.
Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing.
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作者：
O'Rawe J;Jiang T;Sun G;Wu Y;Wang W;Hu J;Bodily P;Tian L;Hakonarson H;Johnson WE;Wei Z;Wang K;Lyon GJ
为了通过下一代测序促进基因组医学的临床实施，获得准确和一致的个人基因组变异呼叫将是至关重要的。用于变量调用的多种软件工具是可用的，但是这些工具的可比性如何，或者它们在实际场景中的相对优点是什么，都不清楚。我们使用商业试剂盒（Illumina HiSeq 2000平台和Agilent SureSelect version 2捕获试剂盒）对来自四个家族的15个外显子组进行测序，平均覆盖率约为120X。我们使用接近默认的参数和五种不同的校准和变量调用管道（SOAP、BWA-GATK、BWA-SNVer、GNUMAP和BWA-SAMtools）分析了原始数据。此外，我们使用Complete Genomics （CG）的测序和分析管道对单个全基因组进行了测序，其中95%的外显子组区域每个碱基被20个或更多的reads覆盖。最后，我们在MiSeq平台上通过扩增子测序验证了919个单核苷酸变异（snv）和841个插入和缺失（indel），包括GATK-only、SOAP-only和共享调用的相似片段，平均覆盖率约为5000X。在所有15个外显子组中，5个Illumina管道之间的SNV一致性为57.4%，而0.5至5.1%的变体被称为每个管道独有的。即使在基因组坐标左归一化和间隔20个碱基对之后，三个调用序列之间的序列一致性仅为26.8%。有11%的CG变异落在外显子组测序的目标区域内，这些区域没有被任何基于illumina的外显子组分析管道调用。基于MiSeq平台上的靶向扩增子测序，97.1%、60.2%和99.1%的GATK-only、SOAP-only和shared snv可以被验证，而只有54.0%、44.6%和78.1%的GATK-only、SOAP-only和shared索引可以被验证。此外，我们对两个家庭（一个有四个个体，另一个有七个个体）的分析表明，通过访问来自多代家庭的遗传数据，在变异发现方面获得了额外的准确性。我们的研究结果表明，在基因组医学环境中，在分析个体基因组时应更加谨慎，包括通过仔细检查来解释阳性和阴性结果，特别是对索引。我们提倡更新多代家族的收集和测序，以提高全基因组的整体准确性。
To facilitate the clinical implementation of genomic medicine by next-generation sequencing, it will be critically important to obtain accurate and consistent variant calls on personal genomes. Multiple software tools for variant calling are available, but it is unclear how comparable these tools are or what their relative merits in real-world scenarios might be. We sequenced 15 exomes from four families using commercial kits (Illumina HiSeq 2000 platform and Agilent SureSelect version 2 capture kit), with approximately 120X mean coverage. We analyzed the raw data using near-default parameters with five different alignment and variant-calling pipelines (SOAP, BWA-GATK, BWA-SNVer, GNUMAP, and BWA-SAMtools). We additionally sequenced a single whole genome using the sequencing and analysis pipeline from Complete Genomics (CG), with 95% of the exome region being covered by 20 or more reads per base. Finally, we validated 919 single-nucleotide variations (SNVs) and 841 insertions and deletions (indels), including similar fractions of GATK-only, SOAP-only, and shared calls, on the MiSeq platform by amplicon sequencing with approximately 5000X mean coverage. SNV concordance between five Illumina pipelines across all 15 exomes was 57.4%, while 0.5 to 5.1% of variants were called as unique to each pipeline. Indel concordance was only 26.8% between three indel-calling pipelines, even after left-normalizing and intervalizing genomic coordinates by 20 base pairs. There were 11% of CG variants falling within targeted regions in exome sequencing that were not called by any of the Illumina-based exome analysis pipelines. Based on targeted amplicon sequencing on the MiSeq platform, 97.1%, 60.2%, and 99.1% of the GATK-only, SOAP-only and shared SNVs could be validated, but only 54.0%, 44.6%, and 78.1% of the GATK-only, SOAP-only and shared indels could be validated. Additionally, our analysis of two families (one with four individuals and the other with seven), demonstrated additional accuracy gained in variant discovery by having access to genetic data from a multi-generational family. Our results suggest that more caution should be exercised in genomic medicine settings when analyzing individual genomes, including interpreting positive and negative findings with scrutiny, especially for indels. We advocate for renewed collection and sequencing of multi-generational families to increase the overall accuracy of whole genomes.
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影响因子：
16.2
作者：
Iossifov I;Ronemus M;Levy D;Wang Z;Hakker I;Rosenbaum J;Yamrom B;Lee YH;Narzisi G;Leotta A;Kendall J;Grabowska E;Ma B;Marks S;Rodgers L;Stepansky A;Troge J;Andrews P;Bekritsky M;Pradhan K;Ghiban E;Kramer M;Parla J;Demeter R;Fulton LL;Fulton RS;Magrini VJ;Ye K;Darnell JC;Darnell RB;Mardis ER;Wilson RK;Schatz MC;McCombie WR;Wigler M
通讯作者：
Wigler M
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：
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影响因子：
1.7
作者：
Carnevali, Paolo;Baccash, Jonathan;Drmanac, Radoje
通讯作者：
Drmanac, Radoje
影响因子：
7
作者：
Li, Ruiqiang;Zhu, Hongmei;Wang, Jun
通讯作者：
Wang, Jun
使用下一代 DNA 测序数据进行变异发现和基因分型的框架。
影响因子：
30.8
作者：
通讯作者：
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