Low linkage disequilibrium indicative of recombination in foot-and-mouth disease virus gene sequence alignments
Bibliographic record
Abstract
We have applied tests for detecting recombination to genes of foot-and-mouth disease virus (FMDV). Our approach estimated summary statistics of linkage disequilibrium (LD), which are sensitive to recombination. Using the genealogical relationships, rate heterogeneity and mutation parameters estimated from individual sets of aligned gene sequences, we simulated matching RNA sequence datasets without recombination. These simulated datasets allowed for recurrent mutations at any site to mimic homoplasy in virus sequence data and allow construction of null distributions for LD parameters expected in the absence of recombination. We tested for recombination in two ways: by comparing LD in observed data with corresponding null distributions obtained from simulated data; and by testing for a negative relationship between observed LD between pairs of polymorphic nucleotide sites and inter-site distance. We applied these tests to six FMDV datasets from four serotypes and found some evidence for recombination in all of them.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".