Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data
Bibliographic record
Abstract
The complete telomere-to-telomere human genome assembly (T2T-CHM13) and the draft human pangenome reference provide unique opportunities to refine DNA methylation (DNAm) studies. Here, we find that T2T-CHM13 calls 7.4% more CpGs genome wide compared to GRCh38 across four widely used short-read DNAm profiling methods and improves the evaluation of probe cross-reactivity and mismatch for Illumina DNAm arrays, yielding new and more reproducible sets of unambiguous probes. The pangenome reference further expands CpG calling by 4.5% in short-read sequencing data and identifies cross-population and population-specific unambiguous probes in DNAm arrays, owing to its improved representation of genetic diversity. These benefits facilitate the discovery of biologically relevant DNAm alterations in epigenome-wide association studies (EWASs). For instance, additional DNAm alterations enriched in cancer-related genes and pathways are identified in cancer EWASs. Together, this study highlights the practical applications of T2T-CHM13 and pangenome for genome biology and provides a basis for expansion of DNAm investigations.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".