Physical map-assisted whole-genome shotgun sequence assemblies
Bibliographic record
Abstract
We describe a targeted approach to improve the contiguity of whole-genome shotgun sequence (WGS) assemblies at run-time, using information from Bacterial Artificial Chromosome (BAC)-based physical maps. Clone sizes and overlaps derived from clone fingerprints are used for the calculation of length constraints between any two BAC neighbors sharing 40% of their size. These constraints are used to promote the linkage and guide the arrangement of sequence contigs within a sequence scaffold at the layout phase of WGS assemblies. This process is facilitated by FASSI, a stand-alone application that calculates BAC end and BAC overlap length constraints from clone fingerprint map contigs created by the FPC package. FASSI is designed to work with the assembly tool PCAP, but its output can be formatted to work with other WGS assembly algorithms able to use length constraints for individual clones. The FASSI method is simple to implement, potentially cost-effective, and has resulted in the increase of scaffold contiguity for both the Drosophila melanogaster and Cryptococcus gattii genomes when compared to a control assembly without map-derived constraints. A 6.5-fold coverage draft DNA sequence of the Pan troglodytes (chimpanzee) genome was assembled using map-derived constraints and resulted in a 26.1% increase in scaffold contiguity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".