Enrichment of a specific polyadenylated RNA for nanopore direct RNA sequencing (RNA SPACE) v1
Bibliographic record
Abstract
This RNA Sequence Picking After Cutting Enzymatically (RNA SPACE) protocol is intended to enrich for a specific polyadenylated RNA, to be performed before the Oxford Nanopore Technologies (ONT) direct RNA sequencing protocol. This could be used to promote sequencing of a low abundance polyadenylated transcript in a mixture (e.g. polyadenylated viral RNA in a human clinical sample), or to elucidate the unknown 5' of a transcript (i.e. replacement for 5' RACE sequencing). This methods should become increasingly valuable as lower throughput nanopore devices such as the Flongle, Plongle and SmidgION get official support for direct RNA sequencing. The RNA SPACE protocol takes advantage of the unusual property of six DNA restriction enzymes (AvaII, AvrII, BanI, HaeIII, HinfI and Taq1) to cut the RNA strand in RNA:DNA duplexes. This introduces a 3' end that is uniquely targetable using the Oxford Nanopore Technologies protocol's sequence-specific "RTA Oligo B" probe option, rather than the standard poly(dT) overhang version of "RTA Oligo B" which pulls down all polyadenylated transcripts. The RNA SPACE software designs two oligonucleotide (oligo) probes for this protocol, for any given gene: the "RE" oligo to generate a RNA:DNA duplex in the known transcripts of interest the sequence-specific RTA Oligo B
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".