Ye Zhan, Kadolph Christopher, Strenn Robert, Wall Daniel, McPherson Elizabeth, Lin Simon
Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.
Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.
Comput Biol Med. 2016 Jan 1;68:165-9. doi: 10.1016/j.compbiomed.2015.03.028. Epub 2015 Apr 8.
Identification and evaluation of incidental findings in patients following whole exome (WGS) or whole genome sequencing (WGS) is challenging for both practicing physicians and researchers. The American College of Medical Genetics and Genomics (ACMG) recently recommended a list of reportable incidental genetic findings. However, no informatics tools are currently available to support evaluation of incidental findings in next-generation sequencing data.
The Wisconsin Hierarchical Analysis Tool for Incidental Findings (WHATIF), was developed as a stand-alone Windows-based desktop executable, to support the interactive analysis of incidental findings in the context of the ACMG recommendations. WHATIF integrates the European Bioinformatics Institute Variant Effect Predictor (VEP) tool for biological interpretation and the National Center for Biotechnology Information ClinVar tool for clinical interpretation.
An open-source desktop program was created to annotate incidental findings and present the results with a user-friendly interface. Further, a meaningful index (WHATIF Index) was devised for each gene to facilitate ranking of the relative importance of the variants and estimate the potential workload associated with further evaluation of the variants. Our WHATIF application is available at: http://tinyurl.com/WHATIF-SOFTWARE CONCLUSIONS: The WHATIF application offers a user-friendly interface and allows users to investigate the extracted variant information efficiently and intuitively while always accessing the up to date information on variants via application programming interfaces (API) connections. WHATIF׳s highly flexible design and straightforward implementation aids users in customizing the source code to meet their own special needs.
对于执业医师和研究人员而言，在对患者进行全外显子组测序（WES）或全基因组测序（WGS）之后识别和评估偶然发现具有挑战性。美国医学遗传学与基因组学学会（ACMG）最近推荐了一份可报告的偶然基因发现清单。然而，目前尚无信息学工具可支持对下一代测序数据中的偶然发现进行评估。
开发了威斯康星偶然发现分层分析工具（WHATIF），它是一个基于Windows的独立桌面可执行程序，以支持在ACMG建议的背景下对偶然发现进行交互式分析。WHATIF整合了用于生物学解释的欧洲生物信息学研究所变异效应预测器（VEP）工具和用于临床解释的美国国立生物技术信息中心临床变异数据库（ClinVar）工具。
创建了一个开源桌面程序，用于注释偶然发现并通过用户友好的界面呈现结果。此外，为每个基因设计了一个有意义的指数（WHATIF指数），以促进对变异相对重要性的排名，并估计与变异进一步评估相关的潜在工作量。我们的WHATIF应用程序可在以下网址获取：http://tinyurl.com/WHATIF-SOFTWARE 结论：WHATIF应用程序提供了一个用户友好的界面，允许用户高效且直观地研究提取的变异信息，同时始终通过应用程序编程接口（API）连接访问有关变异的最新信息。WHATIF高度灵活的设计和直接的实现方式有助于用户定制源代码以满足他们自己的特殊需求。
