Rapid Multiplexed Reduced Representation Bisulfite Sequencing Library Prep (rRRBS)
Bibliographic record
Abstract
DNA methylation is a common mechanism of epigenetic regulation involved in transcriptional modulation and genome stability. With the evolution of next-generation sequencing technologies, establishing quantitative genome-wide DNA methylation profiles is becoming routine in many laboratories. However, many of these approaches take several days to accomplish and use subjective PCR methods to amplify sequencing libraries, which can induce amplification bias. Here we propose a rapid Reduced Representation Bisulfite Sequencing (rRRBS) protocol to minimize PCR amplification bias and reduce total time of multiplexed library construction. In this modified approach, the precise quantification of the final library amplification step is accomplished and monitored by qPCR, instead of using standard PCR and gel electrophoresis, to determine the appropriate number of cycles to perform. The main advantages of this rRRBS method are: i) Reduced amount of amplification enzyme used for library prep, ii) Reduced number of PCR cycles resulting in less PCR amplification bias, and iii) Preparation of quality multiplexed rRRBS libraries in only ~2 days.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".