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cellSTAAR: incorporating single-cell-sequencing-based functional data to boost power in rare variant association testing of noncoding regions
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Bibliographic record
VenueNature Methods · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of OttawaMcGill UniversityUniversity of CalgaryUniversité LavalUniversity of SaskatchewanUniversité de MontréalRoyal Ottawa Mental Health CentreProvidence Health Care
FundersNational Institute on Minority Health and Health DisparitiesNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesNational Cancer Institute
KeywordsChromatinBiobankDNA sequencingPrecision medicineGenetic associationAssociation (psychology)ChIA-PETBiological dataGenetic variants
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
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.
metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.438
Threshold uncertainty score0.996
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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.
Opus teacher head0.066
GPT teacher head0.358
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation status
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 teacher head, not a consensus.
Study designBench or experimental
Domainnot available
GenreMethods
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".
Quick stats
Citations0
Published2025
Admission routes1
Has abstractno