Evaluation of gene-based association tests for analyzing rare variants using Genetic Analysis Workshop 18 data
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Bibliographic record
Abstract
The focus of our work is to evaluate several recently developed pooled association tests for rare variants and assess the impact of different gene annotation methods and binning strategies on the analyses of rare variants under Genetic Analysis Workshop 18 real and simulated data settings. We considered the sample of 103 unrelated individuals with sequence data, genotypes of rare variants from chromosome 3, real phenotype of hypertension status and simulated phenotypes of systolic blood pressure (SBP) and diastolic blood pressure (DBP), and covariates of age, sex, and the interaction between age and sex. In the analysis of real phenotype data, we did not obtain significant results for any binning strategy; however, we observed a slight deviation of the p-values from the uniform distribution based on the protein-damaging variant grouping strategy. Evaluation of methods using simulated data showed lack of power even at the conservative level of 0.05 for most of the causal genes on chromosome 3. Nevertheless, analysis of MAP4 produced good power for all tests at various levels of the tests for both DBP and SBP. Our results also confirmed that Fisher's method is not only robust but can also improve power over individual pooled linear and quadratic tests and is often better than other robust tests such as SKAT-O.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it