SeqDB: Biological Collection Management with Integrated DNA Sequence Tracking
Bibliographic record
Abstract
Agriculture and Agri-Food Canada (AAFC) is home to a world-class taxonomy program based on Canada’s national agricultural collections for Botany, Mycology and Entomology. These collections contain valuable resources, such as type specimen for authoritative identification using approaches that include phenotyping, DNA barcoding, and whole genome sequencing. These authoritative references allow for accurate identification of the taxonomic biodiversity found in environmental samples in fields such as metagenomics. AAFC’s internally developed web application, termed SeqDB, tracks the complete workflow and provenance chain from source specimen information through DNA extractions, PCR reactions, and sequencing leading to binary DNA sequence files. In the context of Next Generation Sequencing (NGS) of environmental samples, SeqDB tracks sampling metadata, DNA extractions, and library preparation workflow leading to demultiplexed sequence files. SeqDB implements the Taxonomic Databases Working Group (TDWG) Darwin Core standard Wieczorek et al. 2012 for Biodiversity Occurrence Data, as well as the Genome Standards Consortium (GSC) Minimum Information about any (X) Sequences (MIxS) specification Yilmaz et al. 2011. When coupled with the built-in data standards validation system, this has led to the ability to search consistent metadata across multiple studies. Furthermore, the application enables tracking the physical storage of the aforementioned specimens and their derivative molecular extracts using an integrated barcode printing and reading system. All the information is presented using a graphical user interface that features intuitive molecular workflows as well as a RESTful API that facilitates integration with external applications and programmatic access of the data. The success of SeqDB has been due to the close collaboration with scientists and technicians undertaking molecular research involving the national collection, and the centralization of their data sets in an access controlled relational database implementing internationally recognized standards. We will describe the overall system, and some of our lessons learned in building it.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.055 |
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 source (direct Gemma or distilled Codex), 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".