Comparing genome sequencing technologies to improve rare disease diagnostics: a protocol for the evaluation of a pilot project, Genome-wide Sequencing Ontario
Bibliographic record
Abstract
BACKGROUND: Genome-wide sequencing has emerged as a promising strategy for the timely diagnosis of rare diseases, but it is not yet available as a clinical test performed in Canadian diagnostic laboratories. We describe the protocol for evaluating a 2-year pilot project, Genome-wide Sequencing Ontario, to offer high-quality clinical genome-wide sequencing in Ontario, Canada. METHODS: The Genome-wide Sequencing Ontario protocol was codesigned by the Ontario Ministry of Health, the Hospital for Sick Children in Toronto and the Children's Hospital of Eastern Ontario in Ottawa. Enrolment of a prospective cohort of patients began on Apr. 1, 2021. Eligible cases with blood samples available for the index case and both parents (i.e., trios) are randomized to receive exome sequencing or genome sequencing. We will collect patient-level data and ascertain costs associated with the laboratory workflow for exome sequencing and genome sequencing. We will compare point estimates for the diagnostic utility and timeliness of exome sequencing and genome sequencing, and we will determine an incremental cost-effectiveness ratio (expressed as the incremental cost of genome sequencing versus exome sequencing per additional patient with a causal variant detected). INTERPRETATION: Findings from this work will provide robust evidence for the diagnostic utility, cost-effectiveness and timeliness of exome sequencing and genome sequencing, and will be disseminated via academic publications and policy briefs. Findings will inform provincial and cross-provincial policy related to the long-term organization, delivery and reimbursement of clinical-grade genome diagnostics for rare disease.
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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 | 0.154 | 0.156 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.055 | 0.013 |
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".