Zhan Ye1, Christopher Kadolph2, Robert Strenn2, Daniel Wall2, Elizabeth McPherson3, Simon Lin2. 1. Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA. Electronic address: ye.zhan@mcrf.mfldclin.edu. 2. Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA. 3. Department of Medical Genetics Services, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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.
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