Additional file 2 of Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance
Bibliographic record
Abstract
Additional file 2: Figure S1. The allele frequency check of each summary statistics. The allele frequency check of each summary statistics with 1000 bull genome project reference population. The x-axis indicated the allele frequency of the reference panel, the y-axis indicated the allele frequency of the same allele in the examined population. The order are: AgVic somatic cell score for Holstein bulls, AgVic somatic cell score for Holstein cows, AgVic somatic cell score for Jersey bulls, AgVic somatic cell score for Jersey cows, AU clinic mastitis for Holstein bulls, AU clinic mastitis for Jersey bulls, LUKE clinic mastitis for Red bulls, AU somatic cell score for Holstein bulls, AU somatic cell score for Jersey bulls, LUKE somatic cell score for Red bulls, ETH clinic mastitis for Brown Swiss cows, ETH clinic mastitis for Brown Swiss bulls, ETH somatic cell score for Brown Swiss cows, ETH somatic cell score for Brown Swiss bulls, INRAE clinic mastitis for Holstein bulls, INRAE clinic mastitis for Montbeliarde bulls, INRAE clinic mastitis for Normande bulls, INRAE somatic cell score for Holstein bulls, INRAE somatic cell score for Montbeliarde bulls, INRAE somatic cell score for Normande bulls, FBN somatic cell score for Holstein bulls, WUR somatic cell score for Holstein bulls. Figure S2. Lambda-N plot to reveal issues with population stratification. The orange line indicates the optimal λGC = 1.Dots are all below 1.1 indicated no population with inflation. Figure S3. P-Z plot to reveal analytical issues with beta, standard error and P-values. The filtered dataset showing perfect concordance. The order are: AU clinic mastitis for Holstein bulls, AU clinic mastitis for Jersey bulls, LUKE clinic mastitis for Red bulls, ETH clinic mastitis for Brown Swiss cows, ETH clinic mastitis for Brown Swiss bulls, INRAE clinic mastitis for Holstein bulls, INRAE clinic mastitis for Montbeliarde bulls, INRAE clinic mastitis for Normande bulls, AgVic somatic cell score for Holstein bulls, AgVic somatic cell score for Holstein cows, AgVic somatic cell score for Jersey bulls, AgVic somatic cell score for Jersey cows, AU somatic cell score for Holstein bulls, AU somatic cell score for Jersey bulls, LUKE somatic cell score for Red bulls, ETH somatic cell score for Brown Swiss cows, ETH somatic cell score for Brown Swiss bulls,, INRAE somatic cell score for Holstein bulls, INRAE somatic cell score for Montbeliarde bulls, INRAE somatic cell score for Normande bulls, FBN somatic cell score for Holstein bulls, WUR somatic cell score for Holstein bulls. Figure S4. Manhattan plot for meta-analysis of clinic mastitis using METAL software. The red horizontal line indicates the genome-wide significance level [− log10(p) = 8.5]. Figure S5. Manhattan plot for meta-analysis of somatic cell score using METAL software. The red horizontal line indicates the genome-wide significance level [− log10(p) = 8.5]. Figure S6. The copy numbers of the GC copy number variant (CNV) in Nordic Holstein animals (123 bulls). The x-axis is the copy number inferred from the fold-change for the CNV depth relative to other regions of the same chromosome. The y-axis is the number of animals with that copy number. Figure S7. Manhattan plot for meta-analysis of somatic cell score (MR-MEGA_SCS) in the current study and US dataset for the selected chromosomes. The red horizontal line indicates the genome-wide significance level [− log10(p) = 8.5 and -log10(p) = -8.5]. Results from current study are plotted as -log10(p) values in the y-axis, while the US GWAS results as log10(p) values.
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.671 | 0.036 |
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".