V-primer: software for the efficient design of genome-wide InDel and SNP markers from multi-sample variant call format (VCF) genotyping data
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
DNA markers are indispensable tools in genetics and genomics research as well as in crop breeding, particularly for marker-assisted selection. Recent advances in next-generation sequencing technology have made it easier to obtain genome sequences for various crop species, enabling the large-scale identification of DNA polymorphisms among varieties, which in turn has made DNA marker design more accessible. However, existing primer design software is not suitable for designing many types of genome-wide DNA markers from next-generation sequencing data. Here, we describe the development of V-primer, high-throughput software for designing insertion/deletion, cleaved amplified polymorphic sequence, and single-nucleotide polymorphism (SNP) markers. We validated the applicability of these markers in different crops. In addition, we performed multiplex PCR targeted amplicon sequencing using SNP markers designed with V-primer. Our results demonstrate that V-primer facilitates the efficient and accurate design of primers and is thus a useful tool for genetics, genomics, and crop breeding. V-primer is freely available at https://github.com/ncod3/vprimer.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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