Multiphase analysis by linkage, quantitative transmission disequilibrium, and measured genotype: systolic blood pressure in complex Mexican American pedigrees
Bibliographic record
Abstract
We apply a multiphase strategy for pedigree-based genetic analysis of systolic blood pressure data collected in a longitudinal study of large Mexican American pedigrees. In the first phase, we conduct variance-components linkage analysis to identify regions that may harbor quantitative trait loci. In the second phase, we carry out pedigree-based association analysis in a selected region with common and low-frequency variants from genome-wide association studies and whole genome sequencing data. Using sequencing data, we compare approaches to pedigree analysis in a 10 megabase candidate region on chromosome 3 harboring a gene previously identified by a consortium for blood pressure genome-wide association studies. We observe that, as expected, the measured genotype analysis tends to provide larger signals than the quantitative transmission disequilibrium test. We also observe that while linkage signals are contributed by common variants, strong associations are found mainly at rare variants. Multiphase analysis can improve computational efficiency and reduce the multiple testing burden.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".