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Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing

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...

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Autores principales: Noguera-Julian, Marc, Lee, Emma R., Shafer, Robert W., Kantor, Rami, Ji, Hezhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354622/
https://www.ncbi.nlm.nih.gov/pubmed/32575676
http://dx.doi.org/10.3390/v12060666
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author Noguera-Julian, Marc
Lee, Emma R.
Shafer, Robert W.
Kantor, Rami
Ji, Hezhao
author_facet Noguera-Julian, Marc
Lee, Emma R.
Shafer, Robert W.
Kantor, Rami
Ji, Hezhao
author_sort Noguera-Julian, Marc
collection PubMed
description 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.
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spelling pubmed-73546222020-07-23 Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing Noguera-Julian, Marc Lee, Emma R. Shafer, Robert W. Kantor, Rami Ji, Hezhao Viruses Commentary 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. MDPI 2020-06-20 /pmc/articles/PMC7354622/ /pubmed/32575676 http://dx.doi.org/10.3390/v12060666 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Commentary
Noguera-Julian, Marc
Lee, Emma R.
Shafer, Robert W.
Kantor, Rami
Ji, Hezhao
Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title_full Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title_fullStr Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title_full_unstemmed Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title_short Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing
title_sort dry panels supporting external quality assessment programs for next generation sequencing-based hiv drug resistance testing
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354622/
https://www.ncbi.nlm.nih.gov/pubmed/32575676
http://dx.doi.org/10.3390/v12060666
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