High-throughput quantification of splicing isoforms
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
Most human messenger RNAs (mRNAs) are alternatively spliced and many exhibit disease-specific splicing patterns. However, the contribution of most splicing events to the development and maintenance of human diseases remains unclear. As the contribution of alternative splicing events to diagnosis and prognosis is becoming increasingly recognized, it becomes important to develop precise methods to quantify the abundance of these isoforms in clinical samples. Here we present a pipeline for real-time PCR annotation of splicing events (RASE) that allows accurate identification of a large number of splicing isoforms in human tissues. The RASE automatically designed specific primer pairs for 81% of all alternative splicing events in the NCBI build 36 database. Experimentally, the majority of the RASE designed primers resulted in isoform-specific amplification suitable for quantification in human cell lines or in formalin-fixed, paraffin-embedded (FFPE) RNA extract. Using this pipeline it is now possible to rapidly identify splicing isoform signatures in different types of human tissues or to validate complete sets of data generated by microarray expression profiling and deep sequencing techniques.
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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 | 0.000 | 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 | 0.000 | 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