Survey of allelic expression using EST mining
Bibliographic record
Abstract
Cis-acting allelic variation in gene regulation is a source of phenotypic variation. Consequently, recent studies have experimentally screened human genes in an attempt to initiate a catalog of genes possessing cis-acting variants. In this study, we use human EST data in dbEST as the source of allelic expression data, and the HapMap database to provide expected allele frequencies in human populations. We demonstrate a greater concordance of allele frequencies estimated from human ESTs in dbEST with those derived from the CEPH HapMap sample representing Caucasians from northern and western Europe, than population samples obtained in Asia and Africa. Deviations between allele frequencies observed in EST databases and the ones obtained from the CEPH HapMap samples may result from common heritable cis-acting variants altering the relative allele distribution in RNA. We provide in silico as well as experimental evidence that this strategy does allow significant enrichment of genes harboring common heritable cis-acting polymorphisms in linkage disequilibrium with expressed alleles.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".