The global spectrum of protein-coding pharmacogenomic diversity
Bibliographic record
Abstract
Differences in response to medications have a strong genetic component. By leveraging publically available data, the spectrum of such genomic variation can be investigated extensively. Pharmacogenomic variation was extracted from the 1000 Genomes Project Phase 3 data (2504 individuals, 26 global populations). A total of 12 084 genetic variants were found in 120 pharmacogenes, with the majority (90.0%) classified as rare variants (global minor allele frequency <0.5%), with 52.9% being singletons. Common variation clustered individuals into continental super-populations and 23 pharmacogenes contained highly differentiated variants ( F ST >0.5) for one or more super-population comparison. A median of three clinical variants (PharmGKB level 1A/B) was found per individual, and 55.4% of individuals carried loss-of-function variants, varying by super-population (East Asian 60.9%>African 60.1%>South Asian 60.3%>European 49.3%>Admixed 39.2%). Genome sequencing can therefore identify clinical pharmacogenomic variation, and future studies need to consider rare variation to understand the spectrum of genetic diversity contributing to drug response.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".