J Mol Diagn. 2019 Nov 18. pii: S1525-1578(19)30412-X. doi: 10.1016/j.jmoldx.2019.09.007. [Epub ahead of print]
Evaluation of Commercial Next-Generation Sequencing Bioinformatics Software Solutions.
Author information
- 1
- From the Departments of Pathology and Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico. Electronic address: rgullapalli@salud.unm.edu.
Abstract
Next-generation sequencing (NGS) diagnostics continue to expand rapidly in clinical medicine. An ever-expanding menu of molecular biomarkers are deemed important for diagnostic, prognostic, and therapeutic assessment in patients. The increasing role of NGS in the clinic is driven mainly by the falling costs of sequencing. However, the data-intensive nature of NGS makes bioinformatic analysis a major challenge to many clinical laboratories. Critically needed NGS bioinformatics personnel are hard to recruit and retain in small- to mid-size clinical laboratories. Also, NGS software often lacks the scalability necessary for expanded clinical laboratory testing volumes. Commercial software solutions aim to bridge the bioinformatics "barrier" via turnkey informatics solutions tailored specifically for the clinical workplace. Yet, there has been no systematic assessment of these software solutions thus far. This paper presents our end-to-end vendor evaluation experience of commercial NGS bioinformatics solutions. Six different commercial vendor solutions were assessed systematically. Key metrics of NGS software evaluation to aid in the robust assessment of software solutions are described. Comprehensive feedback provided by the TriCore molecular pathology team enabled the final vendor selection. Many key lessons were learned during the software evaluation process, which are described here. This manuscript aims to provide a detailed road map for small- to mid-size clinical laboratories interested in evaluating commercial bioinformatics solutions available in the marketplace.
Copyright © 2019. Published by Elsevier Inc.
- PMID:
- 31751676
- DOI:
- 10.1016/j.jmoldx.2019.09.007
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