A simple modification of library length for highly divergent gene capture
Bibliographic record
Abstract
Abstract Hybridization capture is considered very cost- and time-effective method for enriching a massive amount of target loci distributed separately in a whole genome. However, divergent loci are difficult to enrich for the sequence mismatch between probes and target DNA. After analysis the distributional pattern of divergent loci in mitochondrial genomes (mitogenomes), we notice that the relatively variable regions are intercept by the relatively conservative regions. We propose to extend the length of library to overcome the problem. By using a home-made probe set to bait amphibian mitogeneomes DNA, we demonstrate that using 2 kb DNA libraries generate high sequence coverage in the highly variable regions than using 400 bp DNA libraries. These suggest that longer fragments in the library generally contain both relatively variable regions and relatively conservative regions. The divergent part DNA along with conservative part DNA is captured during hybridization. We present a protocol that allows users to overcome the gap problem for highly divergent gene capture.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.010 |
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".