Abstract
External quality assessment (EQA) is a keystone element in the validation and implementation of next generation sequencing (NGS)-based HIV drug resistance testing (DRT). Software validation and evaluation is a critical element in NGS EQA programs. While the development, sharing, and adoption of wet lab protocols is coupled with the increasing access to NGS technology worldwide, rendering it easy to produce NGS data for HIV-DRT, bioinformatic data analysis remains a bottleneck for most of the diagnostic laboratories. Several computational tools have been made available, via free or commercial sources, to automate the conversion of raw NGS data into an actionable clinical report. Although different software platforms yield equivalent results when identical raw NGS datasets are analyzed for variations at higher abundance, discrepancies arise when variations at lower frequencies are considered. This implies that validation and performance assessment of the bioinformatics tools applied in NGS HIV-DRT is critical, and the origins of the observed discrepancies should be determined. Well-characterized reference NGS datasets with ground truth on the genotype composition at all examined loci and the exact frequencies of HIV variations they may harbor, so-called dry panels, would be essential in such cases. The strategic design and construction of such panels are challenging but imperative tasks in support of EQA programs for NGS-based HIV-DRT and the validation of relevant bioinformatics tools. Here, we present criteria that can guide the design of such dry panels, which were discussed in the Second International Winnipeg Symposium themed for EQA strategies for NGS HIVDR assays.
Highlights
Drug resistance testing (DRT) methods for HIV-1 are continually evolving as exemplified by next generation sequencing (NGS) technology, which is gradually replacing Sanger chemistry in clinical diagnostics [1,2]
The capacity of a laboratory in the effective management of NGS data constitutes an essential component in external quality assessment (EQA) of the laboratory’s competence in performing NGS-based HIV-DRT
Reference materials or proficiency test (PT) panels have long been used in the validation of experimental procedures and EQA applications for laboratories performing Sanger-based HIV-DRT [7,8,9]
Summary
Drug resistance testing (DRT) methods for HIV-1 are continually evolving as exemplified by NGS technology, which is gradually replacing Sanger chemistry in clinical diagnostics [1,2]. The analysis of the large volumes of raw NGS data generated in such tests requires complex and reproducible bioinformatic tools to provide robust and clinically actionable results. Reference materials or proficiency test (PT) panels have long been used in the validation of experimental procedures and EQA applications for laboratories performing Sanger-based HIV-DRT [7,8,9]. Converting large volume raw NGS data, of different quality, into end-user interpretable HIV-DRT reports is, a challenging task. These pipelines share many essential procedures, including filtering of short and poor quality reads, reference alignment, variant calling, drug resistance mutation (DRM) identification, query against selected clinically validated algorithm(s), and a final data reporting step [10,11,12]. Besides its foreseeable EQA application, well-characterized dry panels consisting of data from different samples, of different quality, and representative of the major NGS platforms, would certainly benefit the development and refinement of software tools and serve the technical training needs for conducting such analysis properly
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