Transferability, Reproducibility and Sensitivity of Mutation Quantification by Duplex Sequencing
Bibliographic record
Abstract
Duplex Sequencing (DS) is an ultra-accurate, error-corrected next generation sequencing (ecNGS) technology for mutation analysis. A working group (WG) within Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee is investigating the suitability of ecNGS for regulatory mutagenicity testing, using DS as a model. Initial steps to promote acceptance require demonstrating technical reproducibility across DS-experienced and inexperienced laboratories and establishing the method's sensitivity relative to conventional tests. Thus, the WG conducted a 'reconstruction experiment' to evaluate the transferability, reproducibility, and sensitivity of DS. TwinStrand Biosciences first applied DS to establish mutation frequency (MF) in DNA samples extracted from the livers of an untreated Sprague Dawley rat, or rats treated with either 100 mg/kg/day benzo[a]pyrene (B[a]P) for ten days or 40 mg/kg/day N-ethyl-N-nitrosourea (ENU) for three days. Using the measured MF in these original samples, mixtures were then constructed using the B[a]P- and ENU-treated samples to create "MF standards" with target MFs 1.2-, 1.5-, and 2-fold greater than the untreated control. Aliquots of these standards were distributed to seven laboratories in North America and Europe. DS libraries were prepared by each laboratory and TwinStrand. All eight laboratories met library preparation and assay performance metrics to yield high quality sequencing data with MF in the expected 'MF standard' range. The measured MF and mutation spectra were nearly identical across the laboratories and a 2-fold increase in MF could readily be identified in all labs relative to the untreated controls. The results confirm the high reproducibility and sensitivity of DS for mutagenicity assessment.
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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 | 0.001 | 0.000 |
| 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".