Compendium of genome-wide scans of lipid-related phenotypes
Bibliographic record
Abstract
The genetic dissection of complex inherited diseases is a major challenge. Despite limited success in finding genes, substantial data based on genome-wide scan strategies is now available for a variety of diseases and related phenotypes. This can perhaps best be appreciated in the field of lipid and lipoprotein levels, where the amount of information generated is becoming overwhelming. We have created a database containing the results from whole-genome scans of lipid-related phenotypes undertaken to date. The usefulness of this database is demonstrated by performing a new autosomal genomic scan on apolipoprotein B (apoB), LDL-apoB, and apoA-I levels, measured in 679 subjects of 243 nuclear families. Linkage was tested using both allele-sharing and variance-component methods. Only two loci provided support for linkage with both methods: a LDL-apoB locus on 18q21.32 and an apoA-I locus on 3p25.2. Adding those findings to the database highlighted the fact that the former is reported as a lipid-related locus for the first time, whereas the latter has been observed before. However, concerns arise when displaying all data on the same map, because a large portion of the genome is now covered with loci supported by at least suggestive evidence of linkage.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".