ExPheWas: a browser for gene-based pheWAS associations
Bibliographic record
Abstract
Structured Abstract Motivation The relationship between protein coding genes and phenotypes has the potential to inform on the underlying molecular function in disease etiology. We conducted a phenome-wide association study (pheWAS) of protein coding genes using a principal components analysis-based approach in the UK Biobank. Results We tested the association between 19,114 protein coding gene regions and 1,210 phenotypes including anthropometric measurements, laboratory biomarkers, cancer registry data, hospitalization and death record codes and algorithmically-defined cardiovascular outcomes. We report the pheWAS results in a user-friendly web-based browser. Taking atrial fibrillation, a common cardiac arrhythmia, as an example, ExPheWas identified genes that are known drug targets for the treatment of arrhythmias and genes involved in biological processes implicated in cardiac muscle function. We also identified MYOT as a possible atrial fibrillation gene. Availability and implementation The ExPheWas browser and API are available at http://exphewas.statgen.org/ Contact Marie-Pierre.Dube@mhi-rc.org
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.173 | 0.055 |
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".