Development of a high-density sub-species-specific targeted SNP assay for Rocky Mountain bighorn sheep (<i>Ovis canadensis canadensis</i>)
Bibliographic record
Abstract
Due to their abundance and relative ease of genotyping, single nucleotide polymorphisms (SNPs) are a commonly used molecular marker for contemporary population genetic and genomic studies. A high-density and cost-effective way to type SNP loci is Allegro targeted genotyping (ATG), which is a form of targeted genotyping by sequencing developed and offered by Tecan genomics. One major drawback of this technology is the need for a reference genome and information on SNP loci when designing a SNP assay. However, for some non-model species genomic information from other closely related species can be used. Here we describe our process of developing an ATG assay to target 50,000 SNPs in Rocky Mountain bighorn sheep, using a reference genome from domestic sheep and SNP resources from prior bighorn sheep studies. We successfully developed a high accuracy, high-density, and relatively low-cost SNP assay for genotyping Rocky Mountain bighorn sheep that genotyped ~45,000 SNP loci. These loci were relatively evenly distributed throughout the genome. Furthermore, the assay produced genotypes at tens of thousands of SNP loci when tested on other mountain sheep species and subspecies.
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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".