Performance of two commercially available sequence‐based HIV‐1 genotyping systems for the detection of drug resistance against HIV type 1 group M subtypes
Bibliographic record
Abstract
The use of genotyping assays for the detection and evaluation of drug resistance mutations within the polymerase gene of human immunodeficiency virus type 1 (HIV-1) is becoming increasingly relevant in the clinical management of HIV-1 infection. However, genotypic resistance assays available currently have been optimised for genetic subtype B strains of the virus and many clinical centres are presented with strains from subtypes A, C, and D. In the present report, we compare the performance of two sequence-based commercially available kits, the ViroSeq Genotyping System (Applied Biosystems, Foster City, CA) and the TruGene HIV-1 Genotyping Kit (Visible Genetics, Toronto, Ontario) against a panel of 35 virus isolates from HIV-1 Group M (subtypes A-J). Full-length consensus sequences were generated by the ViroSeq genotyping system for 26 of 31 (83.8%) of the isolates tested, in contrast to the TruGene genotyping system, which generated 16 of 30 (53%) usable sequences overall. Overall, subtype B isolates were sequenced with a greater degree of success than non-subtype B isolates. Discrepancies were found between the consensus sequences reported by each system for each sample (mean difference 1.0%; range 0.0-3.2%), but these appeared to be random and did not affect interpretation of the major resistance codons. In addition, both systems were able to amplify template RNA from low copy viral load plasma samples (10(2)-10(3) RNA copies/ml) taken from a random selection of patient samples encompassing subtypes A-C. While the availability of these genotyping systems should facilitate studies of HIV-1 drug resistance in countries in which these subtypes are prevalent, the performance against subtypes other than B needs to be improved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".