Ultra-low-input native ChIP-seq for rare cell populations
Bibliographic record
Abstract
Combined chromatin immunoprecipitation and next generation sequencing \(ChIP-seq) has become an extremely popular method to generate genome-wide epigenetic pro les from numerous cell lines and tissue types.Typical ChIP-seq experiments require large number of cells, making them ill-adapted to the study of rare cell populations.This procedure describes an ultra-low-input \(ULI) micrococcal nucleasebased native ChIP \(NChIP) and sequencing library construction method to generate genome-wide chromatin pro les from as few as 10 3 cells \(Brind'Amour et al., 10.1038/ncomms7033).In addition, ULI-NChIP-seq has been validated in vivo, by generation of H3K9me3 and H3K27me3 pro les from E13.5 primordial germ cells isolated from single embryos \ (Liu, Brind'Amour et al., 10.1101/gad.244848.114).ULI-NChIP-seq should be useful to generate high quality and complexity libraries from rare cell populations, allowing to decrease colony breeding size or to analyze rare clinical samples.Due to often variable cell numbers obtained during isolation of in vivo cell population, the procedure described here allows for exibility, with some suggestions on adaptation of buffer or volume conditions at various points during the procedure.
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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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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.
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.
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".