Control Genes and Variability: Absence of Ubiquitous Reference Transcripts in Diverse Mammalian Expression Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Control genes, commonly defined as genes that are ubiquitously expressed at stable levels in different biological contexts, have been used to standardize quantitative expression studies for more than 25 yr. We analyzed a group of large mammalian microarray datasets including the NCI60 cancer cell line panel, a leukemia tumor panel, and a phorbol ester induction time course as well as human and mouse tissue panels. Twelve housekeeping genes commonly used as controls in classical expression studies (including GAPD, ACTB, B2M, TUBA, G6PD, LDHA, and HPRT) show considerable variability of expression both within and across microarray datasets. Although we can identify genes with lower variability within individual datasets by heuristic filtering, such genes invariably show different expression levels when compared across other microarray datasets. We confirm these results with an analysis of variance in a controlled mouse dataset, showing the extent of variability in gene expression across tissues. The results show the problems inherent in the classical use of control genes in estimating gene expression levels in different mammalian cell contexts, and highlight the importance of controlled study design in the construction of microarray experiments.
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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 | 0.001 | 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 it