Visualization of consensus genome structure without using a reference genome
Bibliographic record
Abstract
BACKGROUND: Standard graphical tools for whole genome comparison require a reference genome. However, any reference is also subject to annotation biases and rearrangements, and may not serve as the standard except for those of extensively studied model species. To fully exploit the rapidly accumulating sequence data from the recent sequencing technologies, genome comparison without any reference has been anticipated. RESULTS: We introduce a circular genome visualizer to compare complete genomes of closely related species. This tool visualizes the position of orthologous gene clusters rather than actual sequences or their features, thereby achieving the comparative view without using a single reference genome. The essential information is the matrix of orthologous gene clusters whose positions (not sequences) are color-coded in circular graphics. As a demonstration, comparison of 14 Lactobacillus paracasei strains and one L. casei strain revealed not only large-scale rearrangements but also genomic islands that are strain-specific. Comparison of 73 Helicobacter pylori strains confirmed their genetic consistency and also revealed the three general patterns of large-scale genome inversions. CONCLUSIONS: From the ample sequence information in the GenBank/ENA/DDBJ repository, we can reconstruct a genomic consensus for particular species. By visualizing multiple strains at a glance, we can identify conserved as well as strain-specific regions in multiply sequenced genomes. Positional consistency for orthologous genes provides information orthogonal to major sequence features such as the GC content or sequence similarity of marker genes. The positional comparison is therefore useful for identifying large-scale genome rearrangements or gene transfers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".