Performance characteristics of next-generation sequencing for antimicrobial resistance gene detection in genomes and metagenomes
Bibliographic record
Abstract
Abstract Short-read sequencing provides a culture-independent method for the detection of antimicrobial resistance (AMR) genes from single bacterial genomes and metagenomic samples. However, the performance characteristics of these approaches have not been systematically characterized. We compared assembly- and read-based approaches to determine sensitivity, positive predictive value, and sequencing limits of detection required for AMR gene detection in an Escherichia coli ST38 isolate spiked into a synthetic microbial community at varying abundances. Using an assembly-based method the limit of detection was 15X genome coverage. We are confident in AMR gene detection at target relative abundances of 100% to 1%, where a target abundance of 1% would require assembly of approximately 30 million reads to achieve 15X target coverage. Recent studies assessing AMR gene content in metagenomic samples may be inadequately sequenced to achieve high sensitivity. Our study informs future sequencing projects and analytical strategies for genomic and metagenomic AMR gene detection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".