Identification and validation of loss of function variants in clinical contexts
Identification and validation of loss of function variants in clinical contexts
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DOI：
10.1002/mgg3.42
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发表时间：
2014-01-01
影响因子：
2
通讯作者：
Beales, Philip
中科院分区：
文献类型：
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作者：
Lescai, Francesco;Marasco, Elena;Beales, Philip
为外显子组测序数据选择合适的变体调用管道在转化医学项目和临床环境中变得越来越重要。作为伦敦大学学院和大奥蒙德街医院共同努力的一部分，GOSgene促进了基因分析，我们的目标是优化适合我们临床环境的变异呼叫管道。我们实现了GATK/Queue框架，并评估了它的两个调用者的性能：经典的UnifiedGenotyper和新的变异发现工具HaplotypeCaller。我们使用Sequenom技术对两种方法调用的功能丧失（LoF）变体进行了实验验证。UnifiedGenotyper对LoF单核苷酸多态性（snp）的总验证率为97.6%，对插入或缺失（indel）的总验证率为92.0%，而HaplotypeCaller对snp的总验证率为91.7%，对indel的总验证率为55.9%。我们确认GATK/Queue在转化医学和临床环境中是一个可靠的管道。我们得出结论，在我们的工作环境中，UnifiedGenotyper是调用者的选择，作为一种准确的方法，具有高的验证率，容易出错的调用，如LoF变体。最后，我们强调了实验验证的重要性，特别是对于INDELs，作为临床环境中标准管道的一部分。
The choice of an appropriate variant calling pipeline for exome sequencing data is becoming increasingly more important in translational medicine projects and clinical contexts. Within GOSgene, which facilitates genetic analysis as part of a joint effort of the University College London and the Great Ormond Street Hospital, we aimed to optimize a variant calling pipeline suitable for our clinical context. We implemented the GATK/Queue framework and evaluated the performance of its two callers: the classical UnifiedGenotyper and the new variant discovery tool HaplotypeCaller. We performed an experimental validation of the loss-of-function (LoF) variants called by the two methods using Sequenom technology. UnifiedGenotyper showed a total validation rate of 97.6% for LoF single-nucleotide polymorphisms (SNPs) and 92.0% for insertions or deletions (INDELs), whereas HaplotypeCaller was 91.7% for SNPs and 55.9% for INDELs. We confirm that GATK/Queue is a reliable pipeline in translational medicine and clinical context. We conclude that in our working environment, UnifiedGenotyper is the caller of choice, being an accurate method, with a high validation rate of error-prone calls like LoF variants. We finally highlight the importance of experimental validation, especially for INDELs, as part of a standard pipeline in clinical environments.