1. Ask2Me VarHarmonizer: A Python-Based Tool to Harmonize Variants from Cancer Genetic Testing Reports and Map them to the ClinVar Database
- Author
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Liu, Yuxi, Yin, Kanhua, Lamichhane, Basanta, Sandbach, John F., Patel, Gayle, Compagnoni, Gia, Kanak, Richard H., Rosen, Barry, Ondrula, David P., Smith, Linda, Brown, Eric, Gold, Linsey, Whitworth, Pat, App, Colleen, Euhus, David, Semine, Alan, Lyons, S. Dwight, Lazarte, Melford Allan C., Parmigiani, Giovanni, Braun, Danielle, and Hughes, Kevin S.
- Subjects
Quantitative Biology - Quantitative Methods ,Quantitative Biology - Genomics - Abstract
PURPOSE: The popularity of germline genetic panel testing has led to a vast accumulation of variant-level data. Variant names are not always consistent across laboratories and not easily mappable to public variant databases such as ClinVar. A tool that can automate the process of variants harmonization and mapping is needed to help clinicians ensure their variant interpretations are accurate. METHODS: We present a Python-based tool, Ask2Me VarHarmonizer, that incorporates data cleaning, name harmonization, and a four-attempt mapping to ClinVar procedure. We applied this tool to map variants from a pilot dataset collected from 11 clinical practices. Mapping results were evaluated with and without the transcript information. RESULTS: Using Ask2Me VarHarmonizer, 4728 out of 6027 variant entries (78%) were successfully mapped to ClinVar, corresponding to 3699 mappable unique variants. With the addition of 1099 unique unmappable variants, a total of 4798 unique variants were eventually identified. 427 (9%) of these had multiple names, of which 343 (7%) had multiple names within-practice. 99% mapping consistency was observed with and without transcript information. CONCLUSION: Ask2Me VarHarmonizer aggregates and structures variant data, harmonizes names, and maps variants to ClinVar. Performing harmonization removes the ambiguity and redundancy of variants from different sources.
- Published
- 2019