Using long-read sequencing to detect and subtype a case with Temple syndrome
Bibliographic record
Abstract
Temple syndrome is an imprinting disorder resulting from abnormal genomic or epigenomic aberrations of chromosome 14 including maternal uniparental disomy (matUPD), paternal deletion of 14q32, or aberrant methylation of the imprinting control regions at 14q32. Understanding the underlying molecular mechanism is essential to understanding the recurrence risk and physical effects. Currently, diagnosis requires the detection of aberrant methylation and copy number loss via methylation-sensitive assays such as methylation-specific multiplex ligation-dependent probe amplification, and short tandem repeat analysis to detect matUPD and the presence of epimutation. Therefore, a one-step approach that can detect aberrant methylation and underlying genetic mechanisms would be of high clinical value. Here we use nanopore sequencing to delineate the molecular diagnosis of a case with Temple syndrome. We demonstrate the application of nanopore sequencing to detect aberrant methylation and underlying genetic mechanisms simultaneously in this case, thus providing a proof of concept for a one-step approach for molecular diagnosis of this disorder.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".