Genome assembly variation and its implications for gene discovery in nematodes
Bibliographic record
Abstract
Genome assemblers are a critical component of genome science, but the choice of assembly software and protocols can be daunting. Here, we investigate genome assembly variation and its implications for gene discovery across three nematode species-Caenorhabditis bovis, Haemonchus contortus, and Heligmosomoides bakeri-highlighting the critical interplay between assembly choice and downstream genomic analysis. Selecting commonly used genome assemblers, we generated multiple assemblies for each species, analyzing their structure, completeness, and effect on gene family analysis. Our findings demonstrate that assembly variations can significantly affect gene family composition, with notable differences in gene families important in anthelmintic discovery and immunomodulation. Despite broadly similar performance using various assembly metrics, comparisons of assemblies with a single species revealed underlying structural rearrangements and inconsistencies in gene content, which would affect downstream analyses. This emphasizes the need for continuous refinement of genome assemblies and their annotations.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".