Clinical genomics information management software linking cancer genome sequence and clinical decisions

Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, int...

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Veröffentlicht in:Genomics (San Diego, Calif.) Calif.), 2013-09, Vol.102 (3), p.140-147
Hauptverfasser: Watt, Stuart, Jiao, Wei, Brown, Andrew M.K., Petrocelli, Teresa, Tran, Ben, Zhang, Tong, McPherson, John D., Kamel-Reid, Suzanne, Bedard, Philippe L., Onetto, Nicole, Hudson, Thomas J., Dancey, Janet, Siu, Lillian L., Stein, Lincoln, Ferretti, Vincent
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Sprache:eng
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Zusammenfassung:Using sequencing information to guide clinical decision-making requires coordination of a diverse set of people and activities. In clinical genomics, the process typically includes sample acquisition, template preparation, genome data generation, analysis to identify and confirm variant alleles, interpretation of clinical significance, and reporting to clinicians. We describe a software application developed within a clinical genomics study, to support this entire process. The software application tracks patients, samples, genomic results, decisions and reports across the cohort, monitors progress and sends reminders, and works alongside an electronic data capture system for the trial's clinical and genomic data. It incorporates systems to read, store, analyze and consolidate sequencing results from multiple technologies, and provides a curated knowledge base of tumor mutation frequency (from the COSMIC database) annotated with clinical significance and drug sensitivity to generate reports for clinicians. By supporting the entire process, the application provides deep support for clinical decision making, enabling the generation of relevant guidance in reports for verification by an expert panel prior to forwarding to the treating physician. •We describe a software application to link sequencing results to clinical guidance.•Multiple genomic technologies create technical challenges for data integration.•Existing clinical knowledge sources are cumbersome to access with genomic data.•Information management systems can enhance clinical sequencing team effectiveness.
ISSN:0888-7543
1089-8646
DOI:10.1016/j.ygeno.2013.04.007