Validation of a high resolution NGS method for detecting spinal muscular atrophy carriers among phase 3 participants in the 1000 Genomes Project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Spinal muscular atrophy (SMA) is the most common pan-ethnic cause of early childhood death due to mutations in a single gene, SMN1. Most chromosome 5 homologs have a functional gene and dysfunctional copy, SMN2, with a single synonymous base substitution that results in faulty RNA splicing. However, the copy number of SMN1 and SMN2 is highly variable, and one in 60 adults worldwide are SMA carriers. Although population-wide screening is recommended, current SMA carrier tests have not been incorporated into targeted gene panels. METHODS: Here we describe a novel computational protocol for determining SMA carrier status based solely on individual exome data. Our method utilizes a Bayesian hierarchical model to quantify an individual's carrier probability given only his or her SMN1 and SMN2 reads at six loci of interest. RESULTS: We find complete concordance with results obtained with the current qPCR-based testing standard in known SMA carriers and affecteds. We applied our protocol to the phase 3 cohort of the 1,000 Genomes Project and found carrier frequencies in multiple populations consistent with the present literature. CONCLUSION: Our process is a convenient, robust alternative to qPCR, which can easily be integrated into the analysis of large multi-gene NGS carrier screens.
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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 | 0.003 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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 it