Integration of mass cytometry and single-cell RNA-sequencing of cells in bronchoalveolar lavage
Bibliographic record
Abstract
Single-cell RNA sequencing (sc-RNA-seq) is a popular method for characterization of cell populations. However, the relationship between RNA and protein expression in cells is often discordant. Protein-based detection methods, such as cytometry by time-of-flight (CyTOF), can provide complementary data to sc-RNA-seq. We collected bronchoalveolar lavage (BAL) from healthy participants and co-evaluated cell populations and gene/protein expression by applying sc-RNA-seq and CyTOF to the same samples. Cell populations were well correlated between these two platforms, but differences emerged at the sub-population level. Notably, macrophage subtypes did not correlate well; whereas T-lymphocytes did. Gene and protein expression levels were significantly correlated (p < .01). Overall, we recommend CyTOF as a tool to validate sc-RNA-seq data for select proteins and cell populations in BAL samples.
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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".