Evaluation of Oxford Nanopore’s MinION Sequencing Device for Microbial Whole Genome Sequencing Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it