A <scp>registry‐based</scp> population study of the <scp>HLA</scp> in Québec, Canada
Bibliographic record
Abstract
As part of the worldwide effort to better characterize HLA diversity in populations, we have studied the population of Québec in Canada. This province has been defined by a complex history with multiple founder effects and migration patterns. We analyzed the typing data of 3806 individuals registered in Héma-Québec's Registry, which covered most administrative regions in Québec. Typing information was resolved at the second field level of resolution by next-generation sequencing (NGS) or by Sanger sequencing. We used the HLA-net.eu GENE[RATE] tools to estimate allele and two-locus haplotype frequencies for HLA-A, -B, -C, -DRB1, -DQB1, and -DPB1, as well as Hardy-Weinberg equilibrium (HWE), selective neutrality, and linkage disequilibrium. The chord genetic distance was also calculated between administrative regions and was visualized using non-metric multidimensional scaling (NMDS) analysis. While most individual regions were in HWE, HWE was rejected for the province considered as a whole. Some regions exhibited signatures of selection, mostly toward an excess of heterozygotes. Allele and haplotype frequencies revealed outlier regions that strongly differed from the other regions. NMDS plots also showed differences between regions. The administrative regions of the province of Québec displayed heterogeneity in their HLA profiles. This heterogeneity was attributable to differing allele and haplotype specificities by region. In particular, regions 02-Saguenay-Lac-Saint-Jean and 01-Bas-St-Laurent diverged from the rest of the regions. The urban regions 06-Montréal and 13-Laval were very diversified in their HLA profiles. Together, these results will help optimize donor recruitment strategies in Québec.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".