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

被引:2
|
作者
Noguera-Julian, Marc [1 ,2 ]
Lee, Emma R. [3 ]
Shafer, Robert W. [4 ]
Kantor, Rami [5 ]
Ji, Hezhao [3 ,6 ]
机构
[1] Hosp Badalona Germans Trias & Pujol, IrsiCaixa AIDS Res Inst, Badalona 08196, Spain
[2] Univ Vic, Cent Univ Catalonia, Fac Med, Chair AIDS & Related Illnesses,Ctr Hlth & Social, Ctra Roda 70, Vic 08500, Spain
[3] Publ Hlth Agcy Canada, Natl Microbiol Lab, JC Wilt Infect Dis Res Ctr, Natl HIV & Retrovirol Labs, Winnipeg, MB R3E 3R2, Canada
[4] Stanford Univ, Med Sch, Stanford, CA 94305 USA
[5] Brown Univ, Div Infect Dis, Alpert Med Sch, Providence, RI 02903 USA
[6] Univ Manitoba, Rady Fac Hlth Sci, Dept Med Microbiol & Infect Dis, Winnipeg, MB R3E 0J9, Canada
来源
VIRUSES-BASEL | 2020年 / 12卷 / 06期
关键词
HIV; drug resistance testing; next generation sequencing; external quality assessment; dry panel; MUTATIONS;
D O I
10.3390/v12060666
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
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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页数:12
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