Houston Methodist Variant Viewer: An Application to Support Clinical Laboratory Interpretation of Next-generation Sequencing Data for Cancer
Autor: | Jessica S. Thomas, Yunyun Ni, Heather Hendrickson, Michael Greenwood, S. Wesley Long, Paul A. Christensen, Randall J. Olsen, Feifei Bao |
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Jazyk: | angličtina |
Rok vydání: | 2017 |
Předmět: |
0301 basic medicine
Java Interface (Java) Computer science Bioinformatics Health Informatics lcsh:Computer applications to medicine. Medical informatics DNA sequencing Pathology and Forensic Medicine 03 medical and health sciences 0302 clinical medicine molecular pathology lcsh:Pathology computer.programming_language Molecular pathology End user Molecular diagnostics Data science Computer Science Applications 030104 developmental biology Workflow 030220 oncology & carcinogenesis Informatics pathology informatics lcsh:R858-859.7 Original Article next-generation sequencing computer lcsh:RB1-214 |
Zdroj: | Journal of Pathology Informatics Journal of Pathology Informatics, Vol 8, Iss 1, Pp 44-44 (2017) |
ISSN: | 2153-3539 2229-5089 |
Popis: | Introduction: Next-generation-sequencing (NGS) is increasingly used in clinical and research protocols for patients with cancer. NGS assays are routinely used in clinical laboratories to detect mutations bearing on cancer diagnosis, prognosis and personalized therapy. A typical assay may interrogate 50 or more gene targets that encompass many thousands of possible gene variants. Analysis of NGS data in cancer is a labor-intensive process that can become overwhelming to the molecular pathologist or research scientist. Although commercial tools for NGS data analysis and interpretation are available, they are often costly, lack key functionality or cannot be customized by the end user. Methods: To facilitate NGS data analysis in our clinical molecular diagnostics laboratory, we created a custom bioinformatics tool termed Houston Methodist Variant Viewer (HMVV). HMVV is a Java-based solution that integrates sequencing instrument output, bioinformatics analysis, storage resources and end user interface. Results: Compared to the predicate method used in our clinical laboratory, HMVV markedly simplifies the bioinformatics workflow for the molecular technologist and facilitates the variant review by the molecular pathologist. Importantly, HMVV reduces time spent researching the biological significance of the variants detected, standardizes the online resources used to perform the variant investigation and assists generation of the annotated report for the electronic medical record. HMVV also maintains a searchable variant database, including the variant annotations generated by the pathologist, which is useful for downstream quality improvement and research projects. Conclusions: HMVV is a clinical grade, low-cost, feature-rich, highly customizable platform that we have made available for continued development by the pathology informatics community. |
Databáze: | OpenAIRE |
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