An Extensive Analysis of Y-Chromosomal Microsatellite Haplotypes in Globally Dispersed Human Populations
Bibliographic record
Abstract
The genetic variance at seven Y-chromosomal microsatellite loci (or short tandem repeats [STRs]) was studied among 986 male individuals from 20 globally dispersed human populations. A total of 598 different haplotypes were observed, of which 437 (73.1%) were each found in a single male only. Population-specific haplotype-diversity values were.86–.99. Analyses of haplotype diversity and population-specific haplotypes revealed marked population-structure differences between more-isolated indigenous populations (e.g., Central African Pygmies or Greenland Inuit) and more-admixed populations (e.g., Europeans or Surinamese). Furthermore, male individuals from isolated indigenous populations shared haplotypes mainly with male individuals from their own population. By analysis of molecular variance, we found that 76.8 % of the total genetic variance present among these male individuals could be attributed to genetic differences between male individuals who were members of the same population. Haplotype sharing between populations, FST statistics, and phylogenetic analysis identified close genetic affinities among Eu-ropean populations and among New Guinean populations. Our data illustrate that Y-chromosomal STR haplotypes are an ideal tool for the study of the genetic affinities between groups of male subjects and for detection of population structure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".