Children's Hospital Informatics Program, Children's Hospital, Boston, Massachusetts, USA.
Genet Med. 2012 Apr;14(4):399-404. doi: 10.1038/gim.2011.68. Epub 2012 Feb 9.
With the advent of whole-genome sequencing made clinically available, the number of incidental findings is likely to rise. The false-positive incidental findings are of particular clinical concern. We provide estimates on the size of these false-positive findings and classify them into four broad categories.
Whole-genome sequences (WGS) of nine individuals were scanned with several comprehensive public annotation databases and average estimates for the number of findings. These estimates were then evaluated in the perspective of various sources of false-positive annotation errors.
At present there are four main sources of false-positive incidental findings: erroneous annotations, sequencing error, incorrect penetrance estimates, and multiple hypothesis testing. Of these, the first two are likely to be addressed in the near term. Conservatively, current methods deliver hundreds of false-positive incidental findings per individual.
The burden of false-positives in whole-genome sequence interpretation threatens current capabilities to deliver clinical-grade whole-genome clinical interpretation. A new generation of population studies and retooling of the clinical decision-support approach will be required to overcome this threat.
随着全基因组测序在临床上的应用，偶然发现的数量可能会增加。假阳性偶然发现尤其具有临床意义。我们对这些假阳性发现的大小进行了估计，并将其分为四大类。
使用几个综合公共注释数据库对 9 个人的全基因组序列（WGS）进行了扫描，并对发现的数量进行了平均估计。然后，从各种假阳性注释错误来源的角度评估了这些估计。
目前有四个主要的假阳性偶然发现来源：错误的注释、测序错误、错误的外显率估计和多重假设检验。其中，前两者在不久的将来可能会得到解决。保守地说，目前的方法会为每个人产生数百个假阳性偶然发现。
全基因组序列解释中的假阳性负担威胁到目前提供全基因组临床解释的能力。需要进行新一代的人群研究和临床决策支持方法的重新调整，以克服这一威胁。
