Abstract
Rapid identification of clinically significant variants is key to the successful application of next generation sequencing technologies in clinical practice. The Melbourne Genomics Health Alliance (MGHA) variant prioritization framework employs a gene prioritization index based on clinician-generated a priori gene lists, and a variant prioritization index (VPI) based on rarity, conservation and protein effect. We used data from 80 patients who underwent singleton whole exome sequencing (WES) to test the ability of the framework to rank causative variants highly, and compared it against the performance of other gene and variant prioritization tools. Causative variants were identified in 59 of the patients. Using the MGHA prioritization framework the average rank of the causative variant was 2.24, with 76% ranked as the top priority variant, and 90% ranked within the top five. Using clinician-generated gene lists resulted in ranking causative variants an average of 8.2 positions higher than prioritization based on variant properties alone. This clinically driven prioritization approach significantly outperformed purely computational tools, placing a greater proportion of causative variants top or in the top 5 (permutation P-value=0.001). Clinicians included 40 of the 49 WES diagnoses in their a priori list of differential diagnoses (81%). The lists generated by PhenoTips and Phenomizer contained 14 (29%) and 18 (37%) of these diagnoses respectively. These results highlight the benefits of clinically led variant prioritization in increasing the efficiency of singleton WES data analysis and have important implications for developing models for the funding and delivery of genomic services.
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Acknowledgements
We would like to acknowledge the Melbourne Genomics Health Alliance Steering Group, Genomics and Bioinformatics Advisory Group and the Clinical Interpretation Reporting Group for establishing the systems and standards applied in this study. The study was funded by the founding organizations of the Melbourne Genomics Health Alliance (Royal Melbourne Hospital, Royal Children’s Hospital, University of Melbourne, Walter and Eliza Hall Institute, Murdoch Childrens Research Institute, Australian Genome Research Facility and CSIRO) and the State Government of Victoria (Department of Health and Human Services). The involvement of AGRF was supported by sponsorship from Bioplatforms Australia and the NCRIS program.
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Stark, Z., Dashnow, H., Lunke, S. et al. A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data. Eur J Hum Genet 25, 1268–1272 (2017). https://doi.org/10.1038/ejhg.2017.123
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DOI: https://doi.org/10.1038/ejhg.2017.123
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