Systematic evaluation of isoform function in literature reports of alternative splicing
Bibliographic record
Abstract
ABSTRACT Although most mammalian genes have multiple isoforms, an ongoing debate is whether these isoforms are all functional as well as the extent to which they increase the genome’s functional repertoire. To ground this debate in data, we established a curation framework for evaluating experimental evidence of functionally distinct splice isoforms (FDSIs) and analyzed splice isoform function for over 700 human and mouse genes. Despite our bias towards prominently studied genes, we found experimental evidence meeting the classical definition for functionally distinct isoforms for only ~5% of the curated genes. If we relax our criteria, the fraction of genes with support for FDSIs remains low (~13%). We provide evidence that this picture will not change substantially with further curation. Furthermore, many FDSIs did not trace to a specific isoform in Ensembl. Our work has implications for computational analyses of alternative splicing and should help shape research around the role of splicing on gene function from presuming large general effects to acknowledging the need for stronger experimental evidence.
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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 | 0.022 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.045 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".