Additional file 5 of Contribution of genetic and epigenetic changes to escape from X-chromosome inactivation
Bibliographic record
Abstract
Additional file5: Table S16. Top 100 results from an analysis associating XCI status with genotype. See additional files. There are separate sheets for association with Xi/Xa and 450k based XCI status calls, and for comparing to all chromosomes, and just chromosome X. The adjusted p-value is calculated using the Benjamini-Hochberg method. For the sheet associating DNAme based XCI status calls with loci on all chromosomes, we included all 610 significant loci instead of the top 100. I have also included the amount of samples with each XCI status (E for escapes XCI, S for subject to XCI) and each genotype (ref for reference allele, het for heterozygous, alt for alternate allele) (columns E-J). Columns M-N are the ratio of reference to alternate alleles at samples escaping or subject to XCI, with O being the ratio of these two columns and P being the reciprocal of O if it is less than 1, to make comparison easier. This enrichment column (col P) shows enrichment of reference allele at samples with one XCI status over the other. For the DNAme allChr sheet we have also included a column showing the attributable risk per allele.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.497 | 0.116 |
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".