Evaluation of Oxford Nanopore’s MinION Sequencing Device for Microbial Whole Genome Sequencing Applications
Bibliographic record
Abstract
The MinION sequencer (Oxford Nanopore Technologies) is a paradigm shifting device allowing rapid, real time long read sequencing of nucleic acids. Yet external benchmarking of this technologies' capabilities has not been extensively reported, nor has thorough evaluation of its utility for field-based analysis with sub-optimal sample types been described. The aim of this study was to evaluate the capability of the MinION sequencer for bacterial genomic and metagenomic applications, with specific emphasis placed on the quality, yield, and accuracy of generated sequence data. Two independent laboratories at the National Microbiology Laboratory (Public Health Agency of Canada), sequenced a set of microbes in replicate, using the currently available flowcells, sequencing chemistries, and software available at the time of the experiment. Overall sequencing yield and quality improved through the course of this set of experiments. Sequencing alignment accuracy was high reaching 97% for all 2D experiments, though was slightly lower for 1D sequencing (94%). 1D sequencing provided much longer sequences than 2D. Both sequencing chemistries performed equally well in constructing genomic assemblies. There was evidence of barcode cross-over using both the native and PCR barcoding methods. Despite the sub-optimal nature of samples sequenced in the field, sequences attributable to B. anthracis the target organism used in this scenario, could none-the-less be detected. Together, this report showcases the rapid advancement in this technology and its utility in the context of genomic sequencing of microbial isolates of importance to public health.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".