LEM-PCR: a method for determining relative transcript isoform proportions using real-time PCR without a standard curve
Bibliographic record
Abstract
Many genes express multiple transcript isoforms generated by alternative splicing of mRNA. Using real-time PCR, it is straightforward to determine the relative expression level of each isoform independently. However, it is less trivial to determine the relative proportions of different isoforms in a cDNA sample. The relative proportions of different isoforms can be important, as a small change in a highly abundant transcript may be more relevant than a large change in a minimally expressed transcript. Currently, determining the relative proportions of isoforms requires the construction of a standard curve using recombinant plasmid DNA or genomic DNA. As recombinant or genomic DNA standards often amplify with different efficiencies to cDNA samples, they may give under- or overestimations of isoform abundances. The method described in this article uses a titration curve generated from the same cDNA samples measured in the experiment. By using samples with different levels of separate isoforms, it is possible to derive linear equations which, when solved, allow the determination of the proportion of each isoform within the samples under study.
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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".