A High-throughput Pipeline for DNA/RNA/small RNA Purification from Tissue Samples for Sequencing
Bibliographic record
Abstract
High-throughput total nucleic acid (TNA) purification methods based on solid-phase reversible immobilization (SPRI) beads produce TNA suitable for both genomic and transcriptomic applications. Even so, small RNA species, including miRNA, bind weakly to SPRI beads under standard TNA purification conditions, necessitating a separate workflow using column-based methods that are difficult to automate. Here, an SPRI-based high-throughput TNA purification protocol that recovers DNA, RNA and small RNA, called GSC-modified RLT+ Aline bead-based protocol (GRAB-ALL), which incorporates modifications to enhance small RNA recovery is presented. GRAB-ALL was benchmarked against existing nucleic acid purification workflows and GRAB-ALL efficiently purifies TNA, including small RNA, for next-generation sequencing applications in a plate-based format suitable for automated high-throughput sample preparation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.014 |
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".