Additional file 1 of Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole-genome sequence genotypes
Bibliographic record
Abstract
Additional file 1: TableS1. Position distribution and minor allele frequencies of SNPs that passed thegenotype quality control; Table S2. Distribution of significant SNPs of single-traitGWAS; Table S3. Numbers of quantitative trait loci revealed by single-traitGWAS and their overlapping among traits; Table S4. The previously reported andreproduction-associated QTL for the significant SNPs revealed by multiple-traitanalysis of six heifer traits; Table S5. The previously reported andreproduction-associated QTL for the significant SNPs revealed by multiple-traitanalysis of nine cow traits; Table S6. The previously reported andreproduction-associated QTL for the significant SNPs revealed by multiple-traitanalysis of four sire traits; Table S7. Significant SNPs and candidate genesfrom multiple-trait analysis of 14 heifers and cows’ traits; Table S8. Thepreviously reported and reproduction-associated QTL for the significant SNPsrevealed by multiple-trait analysis of 14 heifer and cow traits; Table S9. Thesignificantly enriched GO terms and KEGG from multiple-trait analysis of 18heifers, cows, sire traits; Table S10. Significant SNPs and candidate genesfrom multiple-trait analysis of 18 heifers, cows, sire traits; Table S11. Thepreviously reported and reproduction-associated QTL for the significant SNPsrevealed by multiple-trait analysis of 18 heifer, cow, and sire traits; Figure S1. Manhattan plots (left) and Quantile-quantile plots (right) of thesingle-trait GWAS results based on imputed WGS data; Figure S2. Numbers of significant SNPs foreach trait category and their overlaps found by multiple-trait analysis. Figure S3. Significantly enrichedbiological functions of candidate genes revealed by multiple-trait analysis. Figure S4. Potential protein-protein interaction among biologically relevantgenes that were identified for heifer, cow, and sire traits in this study.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.811 | 0.097 |
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".