Deriving Group A Streptococcus Typing Information from Short-Read Whole-Genome Sequencing Data
Bibliographic record
Abstract
Typing of group A Streptococcus (GAS) is crucial for infection control and epidemiology. While whole-genome sequencing (WGS) is revolutionizing the way that bacterial organisms are typed, it is necessary to provide backward compatibility with currently used typing schemas to facilitate comparisons and understanding of epidemiological trends. Here, we sequenced the genomes of 191 GAS isolates representing 42 different emm types and used bioinformatics tools to derive commonly used GAS typing information directly from the short-read WGS data. We show that emm typing and multilocus sequence typing can be achieved rapidly and efficiently using this approach, which also permits the determination of the presence or absence of genes associated with GAS tissue tropism. We also report on how the WGS data analysis was instrumental in identifying ambiguities present in the commonly used emm type database hosted by the U.S. Centers for Disease Control and Prevention.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.002 |
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".