Genome‐wide identity‐by‐descent sharing among CEPH siblings
Bibliographic record
Abstract
The concept of genetic identity-by-descent (IBD) has markedly advanced our understanding of the genetic similarity among relatives and triggered a number of developments in epidemiological genetics. However, no empirical measure of this relatedness throughout the whole human genome has yet been published. Analyzing highly polymorphic genetic variations from the Centre d'études du polymorphisme humain (CEPH) database, we report the first genome-wide estimation of the mean and variation in IBD sharing among siblings. From 1,522 microsatellite markers spaced at an average of 2.3 cM on 498 sibling pairs, we estimated a mean of 0.4994 and a standard deviation of 0.0395. In order to account for the impact of varying chromosomal lengths and recombination rates, the analysis was also performed at the chromosomal and marker levels and for paternal and maternal DNA separately. Based on the variation, we estimate an "effective number of segregating loci" of around 80 for sibling pairs over the whole genome (i.e., the number of loci that would yield the same standard deviation in IBD sharing if all loci were segregating independently). Finally, we briefly assess the impact of genotyping errors on IBD estimations, compare our results to published theoretical and simulated expectations, and discuss some implications of our findings.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".