Reporting results from whole-genome and whole-exome sequencing in clinical practice: a proposal for Canada?
Bibliographic record
Abstract
PURPOSE: This article proposes recommendations for the use of whole-genome and whole-exome (WGS/WES) sequencing in clinical practice, endorsed by the board of directors of the Canadian College of Medical Geneticists. The publication of statements and recommendations by several international and national organisations on clinical WGS/WES has prompted a need for Canadian-specific guidance. METHODS: A multi-disciplinary group consisting of lawyers, ethicists, genetic researchers, and clinical geneticists was assembled to review existing guidelines on WGS/WES and identify provisions relevant to the Canadian context. RESULTS: Definitions were provided to orient the recommendations and to minimize confusion with other recommendations. Recommendations include the following: WGS/WES should be used in a judicious and cost-efficient manner; WGS/WES should be used to answer a clinical question; and physicians need to explain to adult patients the nature of the results that could arise, so as to allow them to make informed choices over whether to take the test and which results they wish to receive. Recommendations are also provided for WGS/WES in the pediatric context, and for when results implicate patients' family members. CONCLUSION: These recommendations are only a proposal to be developed into comprehensive Canadian-based guidelines. They aim to promote discussion about the reporting of WGS/WES results, and to encourage the ethical implementation of these new technologies in the clinical setting.
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.
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 | 0.176 | 0.312 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.018 | 0.024 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.046 | 0.040 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".