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Houston Methodist Variant Viewer: An Application to Support Clinical Laboratory Interpretation of Next-generation Sequencing Data for Cancer

Overview of attention for article published in Journal of Pathology Informatics, November 2017
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Title
Houston Methodist Variant Viewer: An Application to Support Clinical Laboratory Interpretation of Next-generation Sequencing Data for Cancer
Published in
Journal of Pathology Informatics, November 2017
DOI 10.4103/jpi.jpi_48_17
Pubmed ID
Authors

Paul A. Christensen, Yunyun Ni, Feifei Bao, Heather L. Hendrickson, Michael Greenwood, Jessica S. Thomas, S. Wesley Long, Randall J. Olsen

Abstract

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. 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 27%
Other 1 9%
Unspecified 1 9%
Professor 1 9%
Student > Ph. D. Student 1 9%
Other 3 27%
Unknown 1 9%
Readers by discipline Count As %
Engineering 3 27%
Biochemistry, Genetics and Molecular Biology 2 18%
Medicine and Dentistry 2 18%
Unspecified 1 9%
Computer Science 1 9%
Other 0 0%
Unknown 2 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 December 2017.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from Journal of Pathology Informatics
#329
of 409 outputs
Outputs of similar age
#339,453
of 445,887 outputs
Outputs of similar age from Journal of Pathology Informatics
#5
of 7 outputs
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So far Altmetric has tracked 409 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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