Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations
Bibliographic record
Abstract
Latin American populations exhibit high genetic and phenotypic diversity shaped by complex admixture histories, yet remain underrepresented in genomic research. Here, we analyze genome-wide data from 432 urban individuals across 13 regions of Peru, including 346 newly genotyped from the Peruvian Genome Project. We revealed fine-scale population structure and demographic patterns shaped by both ancient and recent events. Indigenous American ancestries in urban individuals trace back to ancient north-south interactions consisted with archaeological records, while admixture events occurring within the last 8-10 generations involved sources already admixed between distinct ancestral lineages. Identity-by-descent analyses reveal sustained gene flow in southern Peru, while effective population size trends highlight demographic stability in Lima over the past 25 generations. Sex-biased admixture patterns suggest Indigenous ancestry contribution preferentially mediated by females. These findings offer a comprehensive view of Peru's genetic heritage, advancing our understanding of human genetic diversity and historical demographic processes in Latin America.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".